Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Jan 1.
Published in final edited form as: J Invest Dermatol. 2023 Jul 5;144(1):43–52.e6. doi: 10.1016/j.jid.2023.06.194

Genomic profiling of the overlap phenotype between psoriasis and atopic dermatitis

Jeong Eun Kim 1,2, Jongmi Lee 3, Yun Jung Huh 1, Katherine Kim 3, Vasuma Chaparala 3, James G Krueger 4, Jaehwan Kim 3,4,5,*
PMCID: PMC11060321  NIHMSID: NIHMS1986174  PMID: 37419444

Abstract

Clinical overlaps between psoriasis and atopic dermatitis (AD) are sometimes undiscernible, and there is no consensus on whether to treat the overlap phenotype as psoriasis or AD. We enrolled 41 patients diagnosed with either psoriasis or AD and clinically re-stratified them into classic psoriasis (n =11), classic AD (n =13), and the overlap phenotype between psoriasis and AD (n=17). We compared the gene expression profiles of lesional and nonlesional skin biopsy tissues and the proteomic profiles of blood samples between the three comparison groups. Global mRNA expression and T-cell subset cytokine expression in the skin and protein biomarker elevation in the blood of the overlap phenotype were consistent with the profiles of psoriasis and different from the profiles of AD. Unsupervised k-means clustering indicated that the best number of distinct clusters for the total population of the three comparison groups was two, and the two clusters of psoriasis and AD were differentiated by gene expression. Our study suggests that clinical overlap phenotype between psoriasis and AD has dominant molecular features of psoriasis, and genomic biomarkers can differentiate psoriasis and AD at molecular levels in patients with a spectrum of psoriasis and AD.

Keywords: Psoriasis, Atopic dermatitis, Genomic comparison, Molecular phenotyping

Introduction

Psoriasis and atopic dermatitis are the two most common chronic inflammatory skin diseases with different clinical features and immunopathogenesis (Guttman-Yassky et al., 2007). Psoriasis patients have well-demarcated thick scaly patches on the scalp, elbows, and knees, and psoriasis is driven by IL-17-producing Th17 stimulated by IL-23 (Guttman-Yassky et al., 2011a, 2011b, Harden et al., 2015, Lowes et al., 2014). Monoclonal antibodies against IL-23, IL-17, and TNF are highly effective in the treatment of psoriasis (Kim and Krueger, 2017). On the other hand, atopic dermatitis patients have eczematous or lichenified patches on flexural areas, and atopic dermatitis has strong Th2 components associated with IL-4 and IL-13 overproduction (Fiset et al., 2006, Guttman-Yassky and Krueger, 2017, Leung, 2000, Leung et al., 2004, Nomura et al., 2003, Ong and Leung, 2006). Monoclonal antibodies against IL-4 receptor subunit α (IL-4Rα) of IL-4 and IL-13 receptors (Hamilton et al., 2014) and monoclonal antibodies against IL-13 (Simpson et al., 2018, Wollenberg et al., 2019) are highly effective for the treatment of atopic dermatitis. In contrast, monoclonal antibodies against IL-17 are not effective for the treatment of atopic dermatitis, including in subsets of patient with atopic dermatitis with higher Th17 activation, such as those with intrinsic atopic dermatitis and Asian patients with atopic dermatitis (Ungar et al., 2021).

However, clinical and histological overlaps between psoriasis and atopic dermatitis, which are sometimes undiscernible even for dermatologists and dermatopathologists, are real-life challenges for patient care (Abramovits et al., 2005, Eyerich et al., 2011, Kapila et al., 2012). The clinical distinction between well-demarcated scaly patches of psoriasis and eczematous or lichenified patches of atopic dermatitis is often ambiguous. The psoriasiform epidermal changes of psoriasis and the epidermal hyperplasia of chronic atopic dermatitis could be found together either in psoriasis or atopic dermatitis skin biopsy tissues, which is described as psoriasiform dermatitis (Christophers, 2001, Krueger and Bowcock, 2005). When clinicians need to choose biologics to treat patients with the overlap phenotype, there is no guideline to decide between biologics approved for psoriasis and biologics approved for atopic dermatitis (Cohen et al., 2020).

To better understand the overlap phenotype between psoriasis and atopic dermatitis, we clinically re-stratified a cohort of patients diagnosed with either psoriasis or atopic dermatitis into classic psoriasis, classic atopic dermatitis, and the overlap phenotype between psoriasis and atopic dermatitis. Next, we compared the gene expression profiles of lesional and nonlesional skin biopsy tissues and proteomic profiles of blood samples among the three comparison groups. By this approach, we characterized (1) dominant genomic profiles of the overlap phenotype compared to classic psoriasis and atopic dermatitis and (2) biomarkers identifying the unsupervised genomic distinction between psoriasis and atopic dermatitis.

Results

Clinical identification of the overlap phenotype between psoriasis and atopic dermatitis in a cohort of patients diagnosed with either psoriasis or atopic dermatitis

The 41 subjects who were diagnosed with either psoriasis or atopic dermatitis at a single institution participated in the study. Three dermatologists examined the clinical findings of the participants and re-stratified them into classic psoriasis (n=11), classic atopic dermatitis (n=13), and the overlap phenotype between psoriasis and atopic dermatitis (n=17) (Figure 1 and Supplementary Figure S1).

Figure 1. Representative clinical photographs of classic psoriasis, classic atopic dermatitis, and the overlap phenotype between psoriasis and atopic dermatitis.

Figure 1.

Open in a new tab

All of the patients consented to the publication of their clinical photographs.

The clinical disease severity of the participants was evaluated by the scoring system for psoriasis (Psoriasis Area and Severity Index (PASI)) and atopic dermatitis (SCORAD: SCORing Atopic Dermatitis and EASI: Eczema Area and Severity Index) simultaneously (Supplementary Table S1). When the disease severity score for psoriasis (PASI) was compared between classic psoriasis and the overlap phenotype, there was no significant difference between them (p > 0.05). In contrast, when the disease severity scores for atopic dermatitis (SCORAD and EASI) were compared between classic atopic dermatitis and the overlap phenotype, the scores were lower in the overlap phenotype than in classic atopic dermatitis (p < 0.05). Consistent with the differences in disease scores for atopic dermatitis, the serum IgE level was also lower in the overlap phenotype compared to classic atopic dermatitis (p < 0.05).

Next, we studied if there were distinct histologic features of the overlap phenotype compared to histologic features of classic psoriasis and atopic dermatitis. The histological differences were evaluated by comparison of typical histologic hallmarks of psoriasis and atopic dermatitis (Supplementary table S2), epidermal thickness (H&E stain, Figure 2a), keratinocyte hyperproliferation (K16 stain, Figure 2b), T-cell accumulation (CD3 stain, Figure 2c), and dendritic cell accumulation (CD11c stain, Figure 2d). When we compared the typical histologic hallmarks of psoriasis and atopic dermatitis, hypogranulosis (100%), elongation of rete ridges (80%), and dermal capillary dilation (90%) were common features in classic psoriasis (Supplementary table S2). Spongiosis (38.5%) and dermal eosinophils (38.5%) were noted in classic atopic dermatitis. However, there were no statistical differences of those findings and other histologic hallmarks of psoriasis and atopic dermatitis between the three comparison groups (p > 0.05). Compared to classic psoriasis or atopic dermatitis, the overlap phenotype showed no significant differences in the epidermal thickness (Figure 2e) and keratinocyte hyperproliferation (Figure 2b).

Figure 2. Histologic comparison between classic psoriasis, classic atopic dermatitis, and the overlap phenotype between psoriasis and atopic dermatitis.

Figure 2.

Open in a new tab

(a) H&E stain, (b) K16 stain, (c) CD3 stain, (d) CD11c stain, (e) epidermal thickness, (f) CD3+ T-cell count, (g) CD11c+ dendritic cell count (Scale bar = 200 μm)

When we measured the mRNA expression of K16 by RT-qPCR, K16 was highly expressed in lesional skin compared to nonlesional skin in the overlap phenotype (False Discovery Rate (FDR) < 0.05), but there was no difference in K16 expression in lesional skin between classic psoriasis, classic atopic dermatitis, and the overlap phenotype (Figure 3). In addition, there was no significant difference in CD3+ T-cell and CD11c+ myeloid dendritic cell accumulation in the epidermis and dermis of the overlap phenotype compared to classic psoriasis or atopic dermatitis (Figure 2f and 2g) (p > 0.05).

Figure 3. Comparison of psoriasis and atopic dermatitis-associated cytokine expression between classic psoriasis, classic atopic dermatitis, and the overlap phenotype between psoriasis and atopic dermatitis.

Figure 3.

Open in a new tab

Differentially expressed cytokines involved in the pathogenesis of psoriasis and atopic dermatitis are measured by RT-PCR (gene expression: Log2 conversion of mRNA expression normalized to human acidic ribosomal protein [HARP], *FDR < 0.05).

Outlining global mRNA expression patterns in the skin of the overlap phenotype between psoriasis and atopic dermatitis

To characterize global mRNA expression patterns of the overlap phenotype, we obtained gene expression profiles from skin biopsy tissues of classic psoriasis lesional skin (n=9) and nonlesional skin (n=7), classic atopic dermatitis lesional skin (n=10) and nonlesional skin (n=10), and the overlap phenotype lesional skin (n=17) and nonlesional skin (n=16) in the study cohort using the Affymetrix Human Genome U133 Plus 2.0 Array (Affymetrix, Santa Clara, CA). The gene expression profiles were normalized with gene expression profiles of control skin from healthy volunteers (n=6) prepared on the same platform by the same investigators (Kim et al., 2016a).

In principal component (PC) analysis, the overlap phenotype lesional skin samples were clustered close to classic psoriasis and atopic dermatitis lesional skin samples, and they were separated from normal control skin samples (Figure 4a). When we studied the differentially expressed genes (DEGs) of lesional skin samples in contrast to normal control skin samples, 81.2% (9,981/12,296) of DEGs was shared between classic psoriasis and the overlap phenotype (Figure 4b and Supplementary Table S3). A lower percentage of 69.3% (8,071/11,644) was shared between classic atopic dermatitis DEGs and the overlap phenotype DEGs.

Figure 4. Global mRNA expression patterns and Gene Set Variation Analysis (GSVA) enrichment scores of immune pathways comparing classic psoriasis, classic atopic dermatitis, and the overlap phenotype between psoriasis and atopic dermatitis.

Figure 4.

Open in a new tab

(a) Principal component analysis and (b) Venn diagram of differentially expressed gene (DEG)s (> 2-fold change and < 0.05 false discovery rate). (c) GSVA enrichment scores of immune pathways. The scores are generated by GSVA with the combined z-score method. Violet, burgundy, and green bars indicate when the expression level of lesional skin vs. normal skin was statistically significant in classic psoriasis, classic atopic dermatitis, and the overlap phenotype between psoriasis and atopic dermatitis, respectively. The gray bar indicates no statistical significance between lesional and normal skin expression levels.

(AD: classic atopic dermatitis, PS: classic psoriasis)

We next computed T helper 1 cells (Th1), Th2, Th17, and T helper 22 cells (Th22) pathway enrichment scores from the global mRNA expression patterns utilizing the Gene Set Variation Analysis (GSVA) (Figure 4c). The enrichment scores of Th1 and Th17 pathways were the highest in classic psoriasis, and the enrichment scores of Th2 and Th22 pathways were the highest in classic atopic dermatitis. The overlap phenotype showed intermediate scores, but the scores were closer to the scores of classic psoriasis.

We further investigated different expression levels of individual DEGs in lesional versus normal skin or lesional vs. nonlesional skin between classic psoriasis, classic atopic dermatitis, and the overlap phenotype (Supplementary Table S3). Most of the DEGs involved in antimicrobial peptides, epidermal hyperplasia, and T cell activation, including S100As, KRT16, and CCR7, were consistently upregulated in lesional skin compared to normal skin in all three groups. In a comparison of lesional versus normal skin, Th17-regulated cytokines (IL17A, CCL20, IL36RN, IL33, IL19, and IL20) and Th1-regulated cytokines (IL12B, CXCL11, and STAT1) were highly expressed in both classic psoriasis and the overlap phenotype (FDR < 0.05) but not in classic atopic dermatitis. In contrast, DEGs involved in Th2-regulated cytokines (IL13RA2, CCL17, CCL26, and CCL27) were highly expressed in classic atopic dermatitis (FDR < 0.05) but not in classic psoriasis and the overlap phenotype.

Quantification of T-cell subset cytokines in the skin of the overlap phenotype between psoriasis and atopic dermatitis

We compared the expression levels of Th17, Th1, Th2, and Th22 cytokines in lesional and nonlesional skin among classic psoriasis, classic atopic dermatitis, and the overlap phenotype by RT-PCR (Supplementary Table S4). Th17 cytokines (IL17A, IL17F, IL17C, NOS2, IL23A, IL36A, IL36G, and CCL20), Th1 cytokines (IFNG, CXCL10, and IL12B), and Th22 cytokine (IL22) were highly expressed in lesional skin compared to nonlesional skin in the overlap phenotype (Figure 3, FDR < 0.05). The expression of Th17 cytokines (IL23A, IL17C, IL36G, and CCL20 in lesional skin; IL17A and NOS2 in nonlesional skin; and IL36A in lesional & nonlesional skin), Th1 cytokines (IFNG and IL12B in lesional skin), and Th22 cytokine (IL22 in lesional skin) of the overlap phenotype was higher than the expression in the paired skin lesions of classic atopic dermatitis (FDR < 0.05). There were no significant differences in the Th17 and Th1 cytokines in the paired skin lesions between classic psoriasis and the overlap phenotype.

The expression of Th2 cytokines (IL4 and CCL27 in lesional skin and IL13 in nonlesional skin) of the overlap phenotype was lower than the expression in the paired skin lesions of classic atopic dermatitis (FDR < 0.05). There were no significant differences in Th2 cytokines in the paired skin lesions between classic psoriasis and the overlap phenotype.

Quantification of psoriasis and atopic dermatitis protein biomarkers in the blood of the overlap phenotype

We compared blood protein biomarkers of psoriasis (Peptidase Inhibitor 3 (PI3) (Elgharib et al., 2019, Guttman-Yassky et al., 2008, Holmannova et al., 2020, Leijten et al., 2021, Wang et al., 2022, Xu et al., 2019), growth differentiation factor 15 (GDF-15) (Akbari et al., 2021, Kaiser et al., 2021), TNFRSF10B (TRAIL-R2) (Peternel et al., 2011)) and atopic dermatitis (Thymus and activation-regulated chemokine (TARC/CCL17) (Kakinuma et al., 2001), MCP-4 (Taha et al., 2000), IL-13 (Tsoi et al., 2019), and aminopeptidase N (AP-N) (Brunner et al., 2017a, Radzikowska et al., 2020) between classic psoriasis, classic atopic dermatitis, and the overlap phenotype (Figure 5). The blood proteomic biomarkers were measured by proximity extension assays (Proseek Multiplex, Olink Proteomics, Upsala, Sweden) (Assarsson et al., 2014, Brunner et al., 2019, Brunner et al., 2017b, Lind et al., 2015).

Figure 5. Comparison of psoriasis and atopic dermatitis protein biomarkers in the blood between classic psoriasis, classic atopic dermatitis, and the overlap phenotype between psoriasis and atopic dermatitis.

Figure 5.

Open in a new tab

Psoriasis biomarkers (PI3, GDF-15. TRAIL-R2) and atopic dermatitis biomarkers (CCL17, MCP-4, IL-13, and AP-N) are measured by proximity extension assays (AD: classic atopic dermatitis, PS: classic psoriasis; *FDR < 0.05, **FDR < 0.01, ***FDR < 0.001).

The levels of blood protein biomarkers of psoriasis (peptidase inhibitor 3, GDF-15, and TRAIL-R2) were increased in the overlap phenotype compared to atopic dermatitis (Figure 5, FDR < 0.05). There was no significant difference in the levels of the blood protein biomarkers of psoriasis between the overlap phenotype and psoriasis (FDR > 0.05). The levels of blood protein biomarkers of atopic dermatitis (CCL17, MCP-4, IL-13, and aminopeptidase N) were decreased in the overlap phenotype compared to atopic dermatitis (Figure 5, FDR < 0.05). There was no significant difference in the levels of the blood protein biomarkers of atopic dermatitis between the overlap phenotype and psoriasis (FDR > 0.05).

Unsupervised k-means clustering of the genomic spectrum between psoriasis and atopic dermatitis

Considering that the genomic profiles of the overlap phenotype were consistent with the genomic profiles of classic psoriasis but different from those of classic atopic dermatitis, we tested if the molecular profiles of the overlap phenotype formed distinct clusters from the molecular profile spectrum of psoriasis and atopic dermatitis. We integrated lesional skin mRNA expression data from classic psoriasis, classic atopic dermatitis, and the overlap phenotype measured by RT-PCR and performed unsupervised k-means clustering analyses. The best number of distinct clusters for the total population was two (Figure 6a). All the classic atopic dermatitis patients (100%) were allocated to Cluster 1 (the atopic dermatitis cluster), and 90.9% of classic psoriasis patients were allocated to Cluster 2 (the psoriasis cluster) (Figure 6b). A total of 70.6% of the overlap phenotype patients were allocated to Cluster 2 (the psoriasis cluster), and 29.4% of them were allocated to Cluster 1 (the atopic dermatitis cluster). When we checked the correlation and the PCs in the total population to identify candidate markers to represent the components, NOS2 and IL36G were positively correlated with PC1, CCL17 was positively correlated with PC2, and CCL27 was negatively correlated with PC 1 (Figure 6c and d). The Gaussian mixture model with NOS2, IL36G, and CCL27 showed distinct two distribution curves in the total population (Figure 6e).

Figure 6. Unsupervised k-means clustering and Gaussian mixture model for the genomic profile spectrum of psoriasis and atopic dermatitis.

Figure 6.

Open in a new tab

(a) Unsupervised k-means clustering with the integrated lesional skin mRNA expression profiles of classic psoriasis, classic atopic dermatitis, and the overlap phenotype. The optimal number of distinct clusters for the total population was two. (b) Proportional bar graphs depicting the distribution of the two molecular clusters in classic atopic dermatitis, classic psoriasis, and the overlap phenotype. (c) Biplot using correlation circle depicting principal component analyses. NOS2, IL36G and CCL27 are representative candidates for PC1 and CCL17 is a representative candidate for PC2. (d) Scatter plot of the candidate marker genes NOS2, IL36G, CCL27, and CCL17. The expression levels of NOS2 and IL36G were positively correlated with PC1 and the expression level of CCL27 was negatively correlated with PC1. The expression level of CCL17 was positively correlated with PC2. (e) The Gaussian mixture model with NOS2, IL36G, and CCL27 showed distinct two distribution curves in the total population. (AD: Atopic dermatitis, PS: Psoriasis, PC: Principal component)

Discussion

The recent concept of viewing psoriasis and atopic dermatitis as a spectrum of disease (Guttman-Yassky and Krueger, 2017) rather than as a dichotomy, came from genomic profiling of clinical and/or pathological overlaps between psoriasis and atopic dermatitis: Kim et al. (Kim et al., 2016b) reported that the dominant type of plaque psoriasis in the Korean population (small plaque psoriasis) has immune signatures of Th2, which overlaps with those of atopic dermatitis. Chen et al. (Chen et al., 2021) also reported that a distinct cluster of psoriasis in the Chinese population has immune signatures of Th2. In the same context but in the opposite direction, Noda et al. (Noda et al., 2015) reported that atopic dermatitis in the Korean population has immune signatures of Th17, which overlaps with those of psoriasis.

There have been case reports of immunologically concomitant psoriasis and atopic dermatitis in the same patients, where biologic agents targeting either Th17 or Th2 are theoretically ineffective (Tsai and Tsai, 2022). However, the question remains whether patients with the clinical overlap phenotype, which may occupy a high proportion of clinically diagnosed atopic dermatitis in Asian countries, have immunologically concomitant psoriasis and atopic dermatitis in the same patients.

To answer the question, we studied a cohort of patients diagnosed with either psoriasis or atopic dermatitis in Seoul, South Korea, where both psoriasis with atopic dermatitis immune signatures (Kim et al., 2016b) and atopic dermatitis with psoriasis immune signatures (Noda et al., 2015) have been reported. Next, we clinically re-stratified the cohort of patients into classic psoriasis, classic atopic dermatitis, and the overlap phenotype, then compared gene expression profiles of lesional and nonlesional skin biopsy tissues and proteomic profiles of blood samples among the three comparison groups. To our knowledge, this is the first genomic profiling of the clinical overlap phenotype within a cohort of patients in the spectrum of psoriasis and atopic dermatitis.

Our study showed that typical histologic hallmarks of psoriasis and atopic dermatitis were not significantly different between classic psoriasis, classic atopic dermatitis, and the overlap phenotype (Supplementary Table S2). When we investigated the differences in CD3+ T-cell and CD11c+ myeloid dendritic cell accumulation in epidermis and dermis among comparison groups, there was higher CD11c+ myeloid dendritic cell accumulation in the dermis of atopic dermatitis compared to the dermis of psoriasis (p < 0.05, Figure 2g) as previously reported (Guttman-Yassky et al., 2007). However, there was no significant difference in CD3+ T-cell and CD11c+ myeloid dendritic cell accumulation in the epidermis and dermis of the overlap phenotype compared to classic psoriasis or atopic dermatitis (Figure 2f and 2g) (p > 0.05). We also observed that long-standing lichenified lesions of atopic dermatitis had histologic findings of psoriasiform epidermal hyperplasia with little or no spongiosis. This finding was consistent with a previous report that Asian atopic dermatitis has more severe epidermal acanthosis than European-American atopic dermatitis (Noda et al., 2015). Clinically confirmed psoriasis frequently shows non-classical histopathologic features, including irregular acanthosis (84%), junctional vacuolar alteration (76%), spongiosis (65%), or hypergranulosis (65%) (Chau et al. 2017).

In contrast to histologic evaluation, global mRNA expression patterns (Figure 4c and Supplementary Table S3), T-cell subset cytokine expression (Figure 3), and blood proteomic markers (Figure 5) distinguished classic psoriasis and atopic dermatitis. In all the genomic and proteomic evaluations, the profiles of the overlap phenotype were consistent with the profiles of classic psoriasis and different from the profiles of classic atopic dermatitis. Therefore, our data propose that the clinical overlap phenotype between psoriasis and atopic dermatitis in the Asian population is more likely to be psoriasis dominant than concomitant psoriasis and atopic dermatitis at the levels of gene expression in the skin and proteomic marker elevation in the blood. For the first choice of biologics to treat patients with the clinical overlap phenotype, our data may support the use of psoriasis biologics targeting the IL-23/Th17 axis rather than atopic dermatitis biologics targeting the Th2 axis.

Retrospective and case studies about concomitant psoriasis and atopic dermatitis have been increasingly reported (Al-Janabi et al., 2020, Barry et al., 2021, Beer et al., 1992, Brumfiel et al., 2022, Cohen et al., 2020, Jaulent et al., 2021, Kirsten et al., 2021, Koschitzky et al., 2021, Mirza et al., 2021, Tsai and Tsai, 2022, Williams and Strachan, 1994), but it was not tested if concomitant psoriasis and atopic dermatitis formulate an independent phenotype distinct from psoriasis and atopic dermatitis at molecular levels. When we performed unsupervised k-means clustering of the total population, including classic psoriasis, classic atopic dermatitis, and the overlap phenotype with integrated gene expression profiles, the best number of distinct clusters for the total population was two (Figure 6a). This may suggest that most of the clinical overlap patients can be subclustered into psoriasis or atopic dermatitis at molecular levels with biomarkers.

The biomarkers that distinguished psoriasis and atopic dermatitis were NOS2, IL36G, and CCL27 (Figures 6c and 6e). NOS2 and IL36G versus CCL27 showed opposite correlation directions in the PC analysis (Figure 6c). NOS2 is an inducible nitric oxidase synthase, and the pathogenicity of nitric oxidase synthase-producing dendritic cells (TNF- and inducible nitric oxide synthase-producing dendritic cells) in psoriasis has been elucidated (Lowes et al., 2005, Zaba et al., 2007). In our study, NOS2 expression was highly associated with hypogranulosis. IL-36G has synergistic effects on the induction of antimicrobial peptides by IL-17A (Carrier et al., 2011, Pfaff et al., 2017), and IL-36G appears to have a central position in the interplay between immune cells and keratinocytes in psoriasis (Vigne et al., 2011). Both NOS2 and IL-36G have been reported as reliable discriminating markers to detect psoriasis over atopic dermatitis (Berekméri et al., 2018, Garzorz-Stark et al., 2016). CCL27 is a critical factor for the development of atopic dermatitis in the keratin-14 IL-4 transgenic mouse model (Chen et al., 2006), whereas CCL27 expression is reportedly decreased in psoriasis epidermis basal keratinocytes (Kim et al., 2021). CCL27 has been reported as a reliable discriminating marker to detect atopic dermatitis over psoriasis (Garzorz-Stark et al., 2016). Our data suggest that a combination of those molecular biomarkers enables subclustering of clinical overlap phenotypes into psoriasis and atopic dermatitis at molecular levels for personalized treatment choice between psoriasis biologics targeting the IL-23/Th17 axis and atopic dermatitis biologics targeting the Th2 axis.

Our study has limitations. Considering the ethnic variation in the prevalence of psoriasis and atopic dermatitis, the genomic profiling of the overlap phenotype needs to be expanded to other ethnicities. Potential confounding effects or effect measure modification by demographic variables, such as age and gender, were not considered in the clustering analyses of molecular profile data. The biomarker approach in this study, which quantified the average expression of preselected genes in the skin and blood, needs to compete with other biomarker approaches, such as single-cell transcriptome or spatial transcriptome for their performance, outcome consistency, and costs to be implemented in the real-world clinical practices (Liu et al., 2022).

In conclusion, our study suggests that patients with histologic findings of psoriasiform dermatitis with combined clinical features of psoriasis and atopic dermatitis may have psoriasis dominant gene expression profiles. A combination of molecular biomarkers, including NOS2, IL36G, and CCL27, distinguishes psoriasis and atopic dermatitis in the cohort of those patients with the ambiguous diagnosis. Our study leads to the treatment hypothesis that targeted treatment with monoclonal antibodies targeting the IL-23/Th17 axis, rather than the current standard treatment with broad immunosuppressants such as cyclosporine and methotrexate, needs to be tested for this group of patients.

Materials & Methods

Detailed experiment methods, statistical analyses, and the list of real-time PCR primers are available in the Supplementary Materials and Methods online.

Study design

The study was approved by the Institutional Review Boards of Hanyang University, Seoul, Korea, and Rockefeller University, New York, NY, USA. Written informed consent was obtained from all patients. Forty-one subjects who were diagnosed with either psoriasis or atopic dermatitis at Hanyang University Hospital, Seoul, Korea, participated in the study. The original diagnoses of the study cohort (n =41) were psoriasis (n =21), atopic dermatitis (n=18), and concomitant psoriasis and atopic dermatitis (n=2). The psoriasis:atopic dermatitis ratio was 1.15:1. The study cohort was re-stratified into classic psoriasis (n=11), classic atopic dermatitis (n=13), and the overlap phenotype between psoriasis and atopic dermatitis (n=17) based on clinical manifestations through physical examination and full skin assessment by three dermatologists. During the re-stratification, 10 cases of psoriasis, 5 of atopic dermatitis, and 2 of concomitant psoriasis and atopic dermatitis cases were classified as the overlap phenotype because of the mixed clinical features of psoriasis and atopic dermatitis and the disagreement of diagnosis (psoriasis or atopic dermatitis) between the three dermatologists. Study subjects did not use any systemic treatments for 4 weeks before or topical treatments for 2 weeks before biopsy.

Supplementary Material

Supplementary Table S1

Supplementary Table S1. Patient demographics and clinical characteristics.

Supplementary Method
Supplementary Figure S1

Supplementary Figure S1. Representative clinical photographs of the overlap phenotype between psoriasis and atopic dermatitis and close-up views of lesional biopsy sites of classic psoriasis, classic atopic dermatitis, and the overlap phenotype. (a, b) Clinical photographs of overlap phenotype patients. Representative photographs of lesional biopsy sites of (c) classic psoriasis (abdomen), (d) classic atopic dermatitis (antecubital area), and (e) the overlap phenotype (back).

Supplementary Table S3

Supplementary Table S3. Differentially expressed genes (DEGs) in tissues from lesional (LS), nonlesional (NL), and normal control skin between classic psoriasis (PS), classic atopic dermatitis (AD), and the overlap phenotype.

Supplementary Table S2

Supplementary Table S2. Histopathologic features of classic psoriasis, overlap phenotype between psoriasis and atopic dermatitis, and classic atopic dermatitis.

Supplementary Table S4

Supplementary Table S4. Primers used for quantitative real-time polymerase chain reaction (RT-qPCR).

Acknowledgement

We thank Professor Seung Sam Paik of the Department of Pathology, Hanyang University College of Medicine, for providing histopathological guidance for the diagnosis. This study was a collaboration project between Hanyang University, Seoul, Korea, and Rockefeller University, New York, USA, and the study was approved by the Institutional Review Boards of Hanyang Univer- sity, Seoul, Korea, and Rockefeller University, New York, USA. Written informed consent was obtained from all patients.

This work was supported, in part, by grant number UL1TR001866 from the National Center for Advancing Translational Sciences (NCATS) and the Na- tional Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) program. JK was supported by the NIAMS K23 Career Development Award (K23AR080043).

Conflicts of Interest

JEK has received research support from Novartis. JK has received research support from Novartis and AbbVie. JGK has received grant support (to The Rockefeller University) from AbbVie, Akros, Allergan, Amgen, Avillion, Baxter, Biogen, Botanix, Boehringer Ingelheim, Bristol-Myers Squibb, Dele- nex, Dermira, Exicure, Innovaderm, Incyte, Janssen, Kadmon, Kineta, Kyowa Kirin, Lilly, Takeda, Lackshmi, Merck, Novan, Novartis, Parexel, Pfizer, Regeneron, Sanofi, Serono, UCB, Vitae Pharmaceuticals, and Xenoport. JGK reports consulting/honoraria from AbbVie, Aclaris, Allergan, Almirall, Amgen, Artax Biopharma, Arena, Aristea, Asana, Aurigene, Biogen Idec, Boehringer Ingelheim, Bristol-Myers Squibb, Escalier, Galapagos, Janssen, Kyowa Kirin, Lilly, MoonLake Immunotherapeutics, Takeda, Novartis, Pfizer, Sanofi, Sienna Biopharmaceuticals, Sun Pharma, Target-Derm, UCB, Valeant, and Ventyx.

The rest of the authors declare that they have no conflict of interest.

Funding Statement

This work was supported, in part, by grant no. UL1TR001866 from the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) program. J.K. was supported by NIAMS K23 Career Development Award (K23AR080043).

Abbreviations:

AD

Atopic dermatitis

DEG

differentially expressed gene

FCH

Fold Change

FDR

False Discovery Rate

GSVA

Gene Set Variation Analysis

IL

Interleukin

LS

lesional

mRNA

Messenger RNA

NL

Nonlesional

PS

Psoriasis

RT-PCR

Reverse transcription polymerase chain reaction

Th1

T Helper 1 cells

Th17

T Helper 17 cells

Th2

T Helper 2 cells

Th22

T Helper 22 cells

Footnotes

Ethics statement

This study was a collaboration project between Hanyang University, Seoul, Korea, and Rockefeller University, New York, NY, USA, and the study was approved by the Institutional Review Boards of Hanyang University, Seoul, Korea, and Rockefeller University, New York, NY, USA. Written informed consent was obtained from all patients.

Availability of data and materials

All the raw microarray data have been deposited in NCBI’s Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/) and are accessible through accession number GSE182740.

REFERENCES

  1. Abramovits W, Cockerell C, Stevenson LC, Goldstein AM, Ehrig T, Menter A. PsEma--a hitherto unnamed dermatologic entity with clinical features of both psoriasis and eczema. Skinmed 2005;4(5):275–81. [DOI] [PubMed] [Google Scholar]
  2. Akbari H, Talaee R, Zaker SF, Nikoueinejad H. Investigating the Correlation between Growth Differentiation Factor 15 Serum Level and Its Gene Expression with Psoriasis and Its Severity. Iran J Allergy Asthma Immunol 2021;20(5):593–9. [DOI] [PubMed] [Google Scholar]
  3. Al-Janabi A, Foulkes AC, Mason K, Smith CH, Griffiths CEM, Warren RB. Phenotypic switch to eczema in patients receiving biologics for plaque psoriasis: a systematic review. J Eur Acad Dermatol Venereol 2020;34(7):1440–8. [DOI] [PubMed] [Google Scholar]
  4. Assarsson E, Lundberg M, Holmquist G, Björkesten J, Thorsen SB, Ekman D, et al. Homogenous 96-plex PEA immunoassay exhibiting high sensitivity, specificity, and excellent scalability. PLoS One 2014;9(4):e95192. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Barry K, Zancanaro P, Casseres R, Abdat R, Dumont N, Rosmarin D. Concomitant atopic dermatitis and psoriasis - a retrospective review. J Dermatolog Treat 2021;32(7):716–20. [DOI] [PubMed] [Google Scholar]
  6. Beer WE, Smith AE, Kassab JY, Smith PH, Rowland Payne CM. Concomitance of psoriasis and atopic dermatitis. Dermatology 1992;184(4):265–70. [DOI] [PubMed] [Google Scholar]
  7. Berekméri A, Latzko A, Alase A, Macleod T, Ainscough JS, Laws P, et al. Detection of IL-36γ through noninvasive tape stripping reliably discriminates psoriasis from atopic eczema. J Allergy Clin Immunol 2018;142(3):988–91.e4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Brumfiel CM, Patel MH, Zirwas MJ. Development of psoriasis during treatment with dupilumab: A systematic review. J Am Acad Dermatol 2022;86(3):708–9. [DOI] [PubMed] [Google Scholar]
  9. Brunner PM, Guttman-Yassky E, Leung DY. The immunology of atopic dermatitis and its reversibility with broad-spectrum and targeted therapies. J Allergy Clin Immunol 2017a;139(4s):S65–s76. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Brunner PM, He H, Pavel AB, Czarnowicki T, Lefferdink R, Erickson T, et al. The blood proteomic signature of early-onset pediatric atopic dermatitis shows systemic inflammation and is distinct from adult long-standing disease. J Am Acad Dermatol 2019;81(2):510–9. [DOI] [PubMed] [Google Scholar]
  11. Brunner PM, Suárez-Fariñas M, He H, Malik K, Wen HC, Gonzalez J, et al. The atopic dermatitis blood signature is characterized by increases in inflammatory and cardiovascular risk proteins. Sci Rep 2017b;7(1):8707. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Carrier Y, Ma HL, Ramon HE, Napierata L, Small C, O’Toole M, et al. Inter-regulation of Th17 cytokines and the IL-36 cytokines in vitro and in vivo: implications in psoriasis pathogenesis. J Invest Dermatol 2011;131(12):2428–37. [DOI] [PubMed] [Google Scholar]
  13. Chen J, Li C, Li H, Yu H, Zhang X, Yan M, et al. Identification of a T(H) 2-high psoriasis cluster based on skin biomarker analysis in a Chinese psoriasis population. J Eur Acad Dermatol Venereol 2021;35(1):150–8. [DOI] [PubMed] [Google Scholar]
  14. Chen L, Lin SX, Agha-Majzoub R, Overbergh L, Mathieu C, Chan LS. CCL27 is a critical factor for the development of atopic dermatitis in the keratin-14 IL-4 transgenic mouse model. Int Immunol 2006;18(8):1233–42. [DOI] [PubMed] [Google Scholar]
  15. Christophers E Psoriasis--epidemiology and clinical spectrum. Clin Exp Dermatol 2001;26(4):314–20. [DOI] [PubMed] [Google Scholar]
  16. Cohen JN, Bowman S, Laszik ZG, North JP. Clinicopathologic overlap of psoriasis, eczema, and psoriasiform dermatoses: A retrospective study of T helper type 2 and 17 subsets, interleukin 36, and β-defensin 2 in spongiotic psoriasiform dermatitis, sebopsoriasis, and tumor necrosis factor α inhibitor-associated dermatitis. J Am Acad Dermatol 2020;82(2):430–9. [DOI] [PubMed] [Google Scholar]
  17. Elgharib I, Khashaba SA, Elsaid HH, Sharaf MM. Serum elafin as a potential inflammatory marker in psoriasis. Int J Dermatol 2019;58(2):205–9. [DOI] [PubMed] [Google Scholar]
  18. Eyerich S, Onken AT, Weidinger S, Franke A, Nasorri F, Pennino D, et al. Mutual antagonism of T cells causing psoriasis and atopic eczema. N Engl J Med 2011;365(3):231–8. [DOI] [PubMed] [Google Scholar]
  19. Fiset PO, Leung DY, Hamid Q. Immunopathology of atopic dermatitis. J Allergy Clin Immunol 2006;118(1):287–90. [DOI] [PubMed] [Google Scholar]
  20. Garzorz-Stark N, Krause L, Lauffer F, Atenhan A, Thomas J, Stark SP, et al. A novel molecular disease classifier for psoriasis and eczema. Exp Dermatol 2016;25(10):767–74. [DOI] [PubMed] [Google Scholar]
  21. Guttman-Yassky E, Krueger JG. Atopic dermatitis and psoriasis: two different immune diseases or one spectrum? Current opinion in immunology 2017;48:68–73. [DOI] [PubMed] [Google Scholar]
  22. Guttman-Yassky E, Lowes MA, Fuentes-Duculan J, Whynot J, Novitskaya I, Cardinale I, et al. Major differences in inflammatory dendritic cells and their products distinguish atopic dermatitis from psoriasis. J Allergy Clin Immunol 2007;119(5):1210–7. [DOI] [PubMed] [Google Scholar]
  23. Guttman-Yassky E, Lowes MA, Fuentes-Duculan J, Zaba LC, Cardinale I, Nograles KE, et al. Low expression of the IL-23/Th17 pathway in atopic dermatitis compared to psoriasis. J Immunol 2008;181(10):7420–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Guttman-Yassky E, Nograles KE, Krueger JG. Contrasting pathogenesis of atopic dermatitis and psoriasis--part I: clinical and pathologic concepts. J Allergy Clin Immunol 2011a;127(5):1110–8. [DOI] [PubMed] [Google Scholar]
  25. Guttman-Yassky E, Nograles KE, Krueger JG. Contrasting pathogenesis of atopic dermatitis and psoriasis--part II: immune cell subsets and therapeutic concepts. J Allergy Clin Immunol 2011b;127(6):1420–32. [DOI] [PubMed] [Google Scholar]
  26. Hamilton JD, Suárez-Fariñas M, Dhingra N, Cardinale I, Li X, Kostic A, et al. Dupilumab improves the molecular signature in skin of patients with moderate-to-severe atopic dermatitis. J Allergy Clin Immunol 2014;134(6):1293–300. [DOI] [PubMed] [Google Scholar]
  27. Harden JL, Krueger JG, Bowcock AM. The immunogenetics of Psoriasis: A comprehensive review. J Autoimmun 2015;64:66–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Holmannova D, Borsky P, Borska L, Andrys C, Hamakova K, Rehacek V, et al. Metabolic Syndrome, Clusterin and Elafin in Patients with Psoriasis Vulgaris. Int J Mol Sci 2020;21(16). [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Jaulent L, Staumont-Sallé D, Tauber M, Paul C, Aubert H, Marchetti A, et al. De novo psoriasis in atopic dermatitis patients treated with dupilumab: a retrospective cohort. J Eur Acad Dermatol Venereol 2021;35(4):e296–e7. [DOI] [PubMed] [Google Scholar]
  30. Kaiser H, Wang X, Kvist-Hansen A, Krakauer M, Gørtz PM, McCauley BD, et al. Biomarkers of subclinical atherosclerosis in patients with psoriasis. Sci Rep 2021;11(1):21438. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Kakinuma T, Nakamura K, Wakugawa M, Mitsui H, Tada Y, Saeki H, et al. Thymus and activation-regulated chemokine in atopic dermatitis: Serum thymus and activation-regulated chemokine level is closely related with disease activity. J Allergy Clin Immunol 2001;107(3):535–41. [DOI] [PubMed] [Google Scholar]
  32. Kapila S, Hong E, Fischer G. A comparative study of childhood psoriasis and atopic dermatitis and greater understanding of the overlapping condition, psoriasis-dermatitis. Australas J Dermatol 2012;53(2):98–105. [DOI] [PubMed] [Google Scholar]
  33. Kim J, Bissonnette R, Lee J, Correa da Rosa J, Suárez-Fariñas M, Lowes MA, et al. The Spectrum of Mild to Severe Psoriasis Vulgaris Is Defined by a Common Activation of IL-17 Pathway Genes, but with Key Differences in Immune Regulatory Genes. J Invest Dermatol 2016a;136(11):2173–82. [DOI] [PubMed] [Google Scholar]
  34. Kim J, Krueger JG. Highly Effective New Treatments for Psoriasis Target the IL-23/Type 17 T Cell Autoimmune Axis. Annu Rev Med 2017;68:255–69. [DOI] [PubMed] [Google Scholar]
  35. Kim J, Lee J, Kim HJ, Kameyama N, Nazarian R, Der E, et al. Single-cell transcriptomics applied to emigrating cells from psoriasis elucidate pathogenic versus regulatory immune cell subsets. J Allergy Clin Immunol 2021;148(5):1281–92. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Kim J, Oh CH, Jeon J, Baek Y, Ahn J, Kim DJ, et al. Molecular Phenotyping Small (Asian) versus Large (Western) Plaque Psoriasis Shows Common Activation of IL-17 Pathway Genes but Different Regulatory Gene Sets. J Invest Dermatol 2016b;136(1):161–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Kirsten N, Mohr N, Maul JT, Augustin M. Incidence of atopic conditions in people with psoriasis: a population-based analysis. Eur J Dermatol 2021;31(1):60–4. [DOI] [PubMed] [Google Scholar]
  38. Koschitzky M, Tan K, Noliza Encarnacion MR, Rivera-Oyola R, Khattri S. Eczematous reactions to psoriasis biologics treated with dupilumab: A case series. JAAD Case Rep 2021;11:29–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Krueger JG, Bowcock A. Psoriasis pathophysiology: current concepts of pathogenesis. Ann Rheum Dis 2005;64 Suppl 2(Suppl 2):ii30–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Leijten E, Tao W, Pouw J, van Kempen T, Olde Nordkamp M, Balak D, et al. Broad proteomic screen reveals shared serum proteomic signature in patients with psoriatic arthritis and psoriasis without arthritis. Rheumatology (Oxford) 2021;60(2):751–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Leung DY. Atopic dermatitis: new insights and opportunities for therapeutic intervention. J Allergy Clin Immunol 2000;105(5):860–76. [DOI] [PubMed] [Google Scholar]
  42. Leung DY, Boguniewicz M, Howell MD, Nomura I, Hamid QA. New insights into atopic dermatitis. J Clin Invest 2004;113(5):651–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Lind L, Ärnlöv J, Lindahl B, Siegbahn A, Sundström J, Ingelsson E. Use of a proximity extension assay proteomics chip to discover new biomarkers for human atherosclerosis. Atherosclerosis 2015;242(1):205–10. [DOI] [PubMed] [Google Scholar]
  44. Liu Y, Wang H, Taylor M, Cook C, Martínez-Berdeja A, North JP, et al. Classification of human chronic inflammatory skin disease based on single-cell immune profiling. Sci Immunol 2022;7(70):eabl9165. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Lowes MA, Chamian F, Abello MV, Fuentes-Duculan J, Lin SL, Nussbaum R, et al. Increase in TNF-alpha and inducible nitric oxide synthase-expressing dendritic cells in psoriasis and reduction with efalizumab (anti-CD11a). Proc Natl Acad Sci U S A 2005;102(52):19057–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Lowes MA, Suárez-Fariñas M, Krueger JG. Immunology of psoriasis. Annu Rev Immunol 2014;32:227–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Mirza FN, Wang A, Ramachandran SM, Damsky W, Cohen JM. Dupilumab-induced phenotype switch from atopic dermatitis to psoriasis is characterized by de novo interleukin-17A expression: a case report. Br J Dermatol 2021;185(2):432–4. [DOI] [PubMed] [Google Scholar]
  48. Noda S, Suárez-Fariñas M, Ungar B, Kim SJ, de Guzman Strong C, Xu H, et al. The Asian atopic dermatitis phenotype combines features of atopic dermatitis and psoriasis with increased TH17 polarization. J Allergy Clin Immunol 2015;136(5):1254–64. [DOI] [PubMed] [Google Scholar]
  49. Nomura I, Goleva E, Howell MD, Hamid QA, Ong PY, Hall CF, et al. Cytokine milieu of atopic dermatitis, as compared to psoriasis, skin prevents induction of innate immune response genes. J Immunol 2003;171(6):3262–9. [DOI] [PubMed] [Google Scholar]
  50. Ong PY, Leung DY. Immune dysregulation in atopic dermatitis. Curr Allergy Asthma Rep 2006;6(5):384–9. [DOI] [PubMed] [Google Scholar]
  51. Peternel S, Prpić-Massari L, Manestar-Blažić T, Brajac I, Kaštelan M. Increased expression of TRAIL and its death receptors DR4 and DR5 in plaque psoriasis. Arch Dermatol Res 2011;303(6):389–97. [DOI] [PubMed] [Google Scholar]
  52. Pfaff CM, Marquardt Y, Fietkau K, Baron JM, Lüscher B. The psoriasis-associated IL-17A induces and cooperates with IL-36 cytokines to control keratinocyte differentiation and function. Sci Rep 2017;7(1):15631. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Radzikowska U, Ding M, Tan G, Zhakparov D, Peng Y, Wawrzyniak P, et al. Distribution of ACE2, CD147, CD26, and other SARS-CoV-2 associated molecules in tissues and immune cells in health and in asthma, COPD, obesity, hypertension, and COVID-19 risk factors. Allergy 2020;75(11):2829–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Simpson EL, Flohr C, Eichenfield LF, Bieber T, Sofen H, Taïeb A, et al. Efficacy and safety of lebrikizumab (an anti-IL-13 monoclonal antibody) in adults with moderate-to-severe atopic dermatitis inadequately controlled by topical corticosteroids: A randomized, placebo-controlled phase II trial (TREBLE). J Am Acad Dermatol 2018;78(5):863–71.e11. [DOI] [PubMed] [Google Scholar]
  55. Taha RA, Minshall EM, Leung DY, Boguniewicz M, Luster A, Muro S, et al. Evidence for increased expression of eotaxin and monocyte chemotactic protein-4 in atopic dermatitis. J Allergy Clin Immunol 2000;105(5):1002–7. [DOI] [PubMed] [Google Scholar]
  56. Tsai YC, Tsai TF. Overlapping Features of Psoriasis and Atopic Dermatitis: From Genetics to Immunopathogenesis to Phenotypes. Int J Mol Sci 2022;23(10). [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Tsoi LC, Rodriguez E, Degenhardt F, Baurecht H, Wehkamp U, Volks N, et al. Atopic Dermatitis Is an IL-13-Dominant Disease with Greater Molecular Heterogeneity Compared to Psoriasis. J Invest Dermatol 2019;139(7):1480–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Ungar B, Pavel AB, Li R, Kimmel G, Nia J, Hashim P, et al. Phase 2 randomized, double-blind study of IL-17 targeting with secukinumab in atopic dermatitis. J Allergy Clin Immunol 2021;147(1):394–7. [DOI] [PubMed] [Google Scholar]
  59. Vigne S, Palmer G, Lamacchia C, Martin P, Talabot-Ayer D, Rodriguez E, et al. IL-36R ligands are potent regulators of dendritic and T cells. Blood 2011;118(22):5813–23. [DOI] [PubMed] [Google Scholar]
  60. Wang X, Kaiser H, Kvist-Hansen A, McCauley BD, Skov L, Hansen PR, et al. IL-17 Pathway Members as Potential Biomarkers of Effective Systemic Treatment and Cardiovascular Disease in Patients with Moderate-to-Severe Psoriasis. Int J Mol Sci 2022;23(1). [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Williams HC, Strachan DP. Psoriasis and eczema are not mutually exclusive diseases. Dermatology 1994;189(3):238–40. [DOI] [PubMed] [Google Scholar]
  62. Wollenberg A, Howell MD, Guttman-Yassky E, Silverberg JI, Kell C, Ranade K, et al. Treatment of atopic dermatitis with tralokinumab, an anti-IL-13 mAb. J Allergy Clin Immunol 2019;143(1):135–41. [DOI] [PubMed] [Google Scholar]
  63. Xu M, Deng J, Xu K, Zhu T, Han L, Yan Y, et al. In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine. Theranostics 2019;9(9):2475–88. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Zaba LC, Cardinale I, Gilleaudeau P, Sullivan-Whalen M, Suarez-Farinas M, Fuentes-Duculan J, et al. Amelioration of epidermal hyperplasia by TNF inhibition is associated with reduced Th17 responses. J Exp Med 2007;204(13):3183–94. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Table S1

Supplementary Table S1. Patient demographics and clinical characteristics.

NIHMS1986174-supplement-Supplementary_Table_S1.docx (19.9KB, docx)
Supplementary Method
NIHMS1986174-supplement-Supplementary_Method.docx (44.5KB, docx)
Supplementary Figure S1

Supplementary Figure S1. Representative clinical photographs of the overlap phenotype between psoriasis and atopic dermatitis and close-up views of lesional biopsy sites of classic psoriasis, classic atopic dermatitis, and the overlap phenotype. (a, b) Clinical photographs of overlap phenotype patients. Representative photographs of lesional biopsy sites of (c) classic psoriasis (abdomen), (d) classic atopic dermatitis (antecubital area), and (e) the overlap phenotype (back).

NIHMS1986174-supplement-Supplementary_Figure_S1.jpg (343.8KB, jpg)
Supplementary Table S3

Supplementary Table S3. Differentially expressed genes (DEGs) in tissues from lesional (LS), nonlesional (NL), and normal control skin between classic psoriasis (PS), classic atopic dermatitis (AD), and the overlap phenotype.

NIHMS1986174-supplement-Supplementary_Table_S3.docx (29.7KB, docx)
Supplementary Table S2

Supplementary Table S2. Histopathologic features of classic psoriasis, overlap phenotype between psoriasis and atopic dermatitis, and classic atopic dermatitis.

NIHMS1986174-supplement-Supplementary_Table_S2.docx (19.3KB, docx)
Supplementary Table S4

Supplementary Table S4. Primers used for quantitative real-time polymerase chain reaction (RT-qPCR).

NIHMS1986174-supplement-Supplementary_Table_S4.docx (15.9KB, docx)

Data Availability Statement

All the raw microarray data have been deposited in NCBI’s Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/) and are accessible through accession number GSE182740.

RESOURCES