Novel factors in the pathogenesis of psoriasis and potential drug candidates are found with systems biology approach

Advances in psoriasis research: From pathogenesis to therapeutics

Psoriasis is a chronic inflammatory condition affecting approximately 2 % to 3 % of the global population. The pathogenesis of psoriasis is complex, involving immune dysregulation, hyperproliferation and angiogenesis. It is a multifactorial disease which is influenced by genetic and environmental factors. The development of various therapeutic agents, such as JAK inhibitors, small molecules, and biologics with potential anti-psoriatic properties was possible with the vast understanding of the pathogenesis of psoriasis. Various signalling pathways, including NF-κB, JAK-STAT, S1P, PDE-4, and A3AR that are involved in the pathogenesis of psoriasis as well as the preclinical models utilised in the research of psoriasis have been highlighted in this review. The review also focuses on technological advancements that have contributed to a better understanding of psoriasis. Then, the molecules targeting the respective signalling pathways that are still under clinical trials or recently approved as well as the latest breakthroughs in therapeutic and drug delivery approaches that can contribute to the improvement in the management of psoriasis are highlighted in this review. This review provides an extensive understanding of the current state of research in psoriasis, giving rise to opportunities for researchers to discover future therapeutic breakthroughs and personalised interventions. Efficient treatment options for individuals with psoriasis can be achieved by an extensive understanding of pathogenesis, therapeutic agents, and novel drug delivery strategies.

Transcriptomic meta-analysis characterizes molecular commonalities between psoriasis and obesity

Despite the abundance of epidemiological evidence for the high comorbid rate between psoriasis and obesity, systematic approaches to common inflammatory mechanisms have not been adequately explored. We performed a meta-analysis of publicly available RNA-sequencing datasets to unveil putative mechanisms that are postulated to exacerbate both diseases, utilizing both late-stage, disease-specific meta-analyses and consensus gene co-expression network (cWGCNA). Single-gene meta-analyses reported several common inflammatory mechanisms fostered by the perturbed expression profile of inflammatory cells. Assessment of gene overlaps between both diseases revealed significant overlaps between up- (n = 170, P value = 6.07 × 10-65) and down-regulated (n = 49, P value = 7.1 × 10-7) genes, associated with increased T cell response and activated transcription factors. Our cWGCNA approach disentangled 48 consensus modules, associated with either the differentiation of leukocytes or metabolic pathways with similar correlation signals in both diseases. Notably, all our analyses confirmed the association of the perturbed T helper (Th)17 differentiation pathway in both diseases. Our novel findings through whole transcriptomic analyses characterize the inflammatory commonalities between psoriasis and obesity implying the assessment of several expression profiles that could serve as putative comorbid disease progression biomarkers and therapeutic interventions.

Integrative systems biology framework discovers common gene regulatory signatures in multiple mechanistically distinct inflammatory skin diseases

More than 20% of the population across the world is affected by non-communicable inflammatory skin diseases including psoriasis, atopic dermatitis, hidradenitis suppurativa, rosacea, etc. Many of these chronic diseases are painful and debilitating with limited effective therapeutic interventions. However, recent advances in psoriasis treatment have improved the effectiveness and provide better management of the disease. This study aims to identify common regulatory pathways and master regulators that regulate molecular pathogenesis. We designed an integrative systems biology framework to identify the significant regulators across several inflammatory skin diseases. With conventional transcriptome analysis, we identified 55 shared genes, which are enriched in several immune-associated pathways in eight inflammatory skin diseases. Next, we exploited the gene co-expression-, and protein-protein interaction-based networks to identify shared genes and protein components in different diseases with relevant functional implications. Additionally, the network analytics unravels 55 high-value proteins as significant regulators in molecular pathogenesis. We believe that these significant regulators should be explored with critical experimental approaches to identify the putative drug targets for more effective treatments. As an example, we identified IKZF1 as a shared significant master regulator in three inflammatory skin diseases, which can serve as a putative drug target with known disease-derived molecules for developing efficacious combinatorial treatments for hidradenitis suppurativa, atopic dermatitis, and rosacea. The proposed framework is very modular, which can indicate a significant path of molecular mechanism-based drug development from complex transcriptomics data and other multi-omics data.

Analysis of the potential relationship between COVID-19 and Behcet's disease using transcriptome data

To investigate the potential role of COVID-19 in relation to Behcet's disease (BD) and to search for relevant biomarkers. We used a bioinformatics approach to download transcriptomic data from peripheral blood mononuclear cells (PBMCs) of COVID-19 patients and PBMCs of BD patients, screened the common differential genes between COVID-19 and BD, performed gene ontology (GO) and pathway analysis, and constructed the protein-protein interaction (PPI) network, screened the hub genes and performed co-expression analysis. In addition, we constructed the genes-transcription factors (TFs)-miRNAs network, the genes-diseases network and the genes-drugs network to gain insight into the interactions between the 2 diseases. We used the RNA-seq dataset from the GEO database (GSE152418, GSE198533). We used cross-analysis to obtain 461 up-regulated common differential genes and 509 down-regulated common differential genes, mapped the PPI network, and used Cytohubba to identify the 15 most strongly associated genes as hub genes (ACTB, BRCA1, RHOA, CCNB1, ASPM, CCNA2, TOP2A, PCNA, AURKA, KIF20A, MAD2L1, MCM4, BUB1, RFC4, and CENPE). We screened for statistically significant hub genes and found that ACTB was in low expression of both BD and COVID-19, and ASPM, CCNA2, CCNB1, and CENPE were in low expression of BD and high expression of COVID-19. GO analysis and pathway analysis was then performed to obtain common pathways and biological response processes, which suggested a common association between BD and COVID-19. The genes-TFs-miRNAs network, genes-diseases network and genes-drugs network also play important roles in the interaction between the 2 diseases. Interaction between COVID-19 and BD exists. ACTB, ASPM, CCNA2, CCNB1, and CENPE as potential biomarkers for 2 diseases.

Construction of a three commitment points for S phase entry cell cycle model and immune-related ceRNA network to explore novel therapeutic options for psoriasis

While competing endogenous RNAs (ceRNAs) play pivotal roles in various diseases, the proliferation and differentiation of keratinocytes are becoming a research focus in psoriasis. Therefore, the three commitment points for S phase entry (CP1-3) cell cycle model has pointed to a new research direction in these areas. However, it is unclear what role ceRNA regulatory mechanisms play in the interaction between keratinocytes and the immune system in psoriasis. In addition, the ceRNA network-based screening of potential therapeutic agents for psoriasis has not been explored. Therefore, we used multiple bioinformatics approaches to construct a ceRNA network for psoriasis, identified CTGF as the hub gene, and constructed a ceRNA subnetwork, after which validation datasets authenticated the results' accuracy. Subsequently, we used multiple online databases and the single-sample gene-set enrichment analysis algorithm, including the CP1-3 cell cycle model, to explore the mechanisms accounting for the increased proliferation and differentiation of keratinocytes and the possible roles of the ceRNA subnetwork in psoriasis. Next, we performed cell cycle and cell trajectory analyses based on a single-cell RNA-seq dataset of psoriatic skin biopsies. We also used weighted gene co-expression network analysis and single-gene batch correlation analysis-based gene set enrichment analysis to explore the functions of CTGF. Finally, we used the Connectivity Map to identify MS-275 (entinostat) as a novel treatment for psoriasis, SwissTargetPrediction to predict drug targets, and molecular docking to investigate the minimum binding energy and binding sites of the drug to target proteins.

Finding Gene Regulatory Networks in Psoriasis: Application of a Tree-Based Machine Learning Approach

Psoriasis is a chronic inflammatory skin disorder. Although it has been studied extensively, the molecular mechanisms driving the disease remain unclear. In this study, we utilized a tree-based machine learning approach to explore the gene regulatory networks underlying psoriasis. We then validated the regulators and their networks in an independent cohort. We identified some key regulators of psoriasis, which are candidates to serve as potential drug targets and disease severity biomarkers. According to the gene regulatory network that we identified, we suggest that interferon signaling represents a key pathway of psoriatic inflammation.

Transcriptional Analysis-Based Alterations Affecting Neuritogenesis of the Peripheral Nervous System in Psoriasis

An increasing amount of evidence indicates the critical role of the cutaneous nervous system in the initiation and maintenance of psoriatic skin lesions by neurogenic inflammation. However, molecular mechanisms affecting cutaneous neurons are largely uncharacterized. Therefore, we reanalyzed a psoriatic RNA sequencing dataset from published transcriptome experiments of nearly 300 individuals. Using the Ingenuity Pathway Analysis software, we associated several hundreds of differentially expressed transcripts (DETs) to nervous system development and functions. Since neuronal projections were previously reported to be affected in psoriasis, we performed an in-depth analysis of neurite formation-related process. Our in silico analysis suggests that SEMA-PLXN and ROBO-DCC-UNC5 regulating axonal growth and repulsion are differentially affected in non-lesional and lesional skin samples. We identified opposing expressional alterations in secreted ligands for axonal guidance signaling (RTN4/NOGOA, NTNs, SEMAs, SLITs) and non-conventional axon guidance regulating ligands, including WNT5A and their receptors, modulating axon formation. These differences in neuritogenesis may explain the abnormal cutaneous nerve filament formation described in psoriatic skin. The processes also influence T-cell activation and infiltration, thus highlighting an additional angle of the crosstalk between the cutaneous nervous system and the immune responses in psoriasis pathogenesis, in addition to the known neurogenic pro-inflammatory mediators.

Lysophosphatidic Acid Mediates Imiquimod-Induced Psoriasis-like Symptoms by Promoting Keratinocyte Proliferation through LPAR1/ROCK2/PI3K/AKT Signaling Pathway

Psoriasis is a chronic inflammatory skin disease. Recently, lysophosphatidic acid (LPA)/LPAR5 signaling has been reported to be involved in both NLRP3 inflammasome activation in macrophages and keratinocyte activation to produce inflammatory cytokines, contributing to psoriasis pathogenesis. However, the effect and molecular mechanisms of LPA/LPAR signaling in keratinocyte proliferation in psoriasis remain unclear. In this study, we investigated the effects of LPAR1/3 inhibition on imiquimod (IMQ)-induced psoriasis-like mice. Treatment with the LPAR1/3 antagonist, ki16425, alleviated skin symptoms in IMQ-induced psoriasis-like mouse models and decreased keratinocyte proliferation in the lesion. It also decreased LPA-induced cell proliferation and cell cycle progression via increased cyclin A2, cyclin D1, cyclin-dependent kinase (CDK)2, and CDK4 expression and decreased p27^Kip1 expression in HaCaT cells. LPAR1 knockdown in HaCaT cells reduced LPA-induced proliferation, suppressed cyclin A2 and CDK2 expression, and restored p27^Kip1 expression. LPA increased Rho-associated protein kinase 2 (ROCK2) expression and PI3K/AKT activation; moreover, the pharmacological inhibition of ROCK2 and PI3K/AKT signaling suppressed LPA-induced cell cycle progression. In conclusion, we demonstrated that LPAR1/3 antagonist alleviates IMQ-induced psoriasis-like symptoms in mice, and in particular, LPAR1 signaling is involved in cell cycle progression via ROCK2/PI3K/AKT pathways in keratinocytes.

Investigation of Omega-3 Polyunsaturated Fatty Acid Biological Activity in a Tissue-Engineered Skin Model Involving Psoriatic Cells

Clinical studies have shown that diets enriched with omega-3 (also know as n-3) polyunsaturated fatty acids could relieve the symptoms of patients with psoriasis. However, the mechanisms involved remain poorly understood. The aim of this study was to investigate the effects of α-linolenic acid (ALA) on the proliferation and differentiation of psoriatic keratinocytes in a three-dimensional skin model. Skin models featuring healthy (healthy substitute) or psoriatic (psoriatic substitute) cells were engineered by the self-assembly method of tissue engineering using a culture medium supplemented with 10 μM ALA in comparison with the regular unsupplemented medium. ALA decreased keratinocyte proliferation and improved psoriatic substitute epidermal differentiation, as measured by decreased Ki67 staining and increased protein expression of FLG and loricrin. The added ALA was notably incorporated into the epidermal phospholipids and metabolized into long-chain n-3 polyunsaturated fatty acids, mainly eicosapentaenoic acid and n-3 docosapentaenoic acid. ALA supplementation led to increased levels of eicosapentaenoic acid derivatives (15-hydroxyeicosapentaenoic acid and 18-hydroxyeicosapentaenoic acid) as well as a decrease in levels of omega-6 (also know as n-6) polyunsaturated fatty acid lipid mediators (9-hydroxyoctadecadienoic acid, 12-hydroxyeicosatetraenoic acid, and leukotriene B₄). Furthermore, the signal transduction mediators extracellular signal‒regulated kinases 1 and 2 were the kinases most activated after ALA supplementation. Taken together, these results show that ALA decreases the pathologic phenotype of psoriatic substitutes by normalizing keratinocyte proliferation and differentiation in vitro.

Transcriptomic landscaping of core genes and pathways of mild and severe psoriasis vulgaris

Psoriasis is a common chronic inflammatory skin disease affecting >125 million individuals worldwide. The therapeutic course for the disease is generally designed upon the severity of the disease. In the present study, the gene expression profile GSE78097, was retrieved from the National Centre of Biotechnology (NCBI)‑Gene Expression Omnibus (GEO) database to explore the differentially expressed genes (DEGs) in mild and severe psoriasis using the Affy package in R software. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways of the DEGs were analysed using clusterProfiler, Bioconductor, version 3.8. In addition, the STRING database was used to develop DEG‑encoded proteins and a protein‑protein interaction network (PPI). Cytoscape software, version 3.7.1 was utilized to construct a protein interaction association network and analyse the interaction of the candidate DEGs encoding proteins in psoriasis. The top 2 hub genes in Cytohubba plugin parameters were validated using immunohistochemical analysis in psoriasis tissues. A total of 382 and 3,001 dysregulated mild and severe psoriasis DEGs were reported, respectively. The dysregulated mild psoriasis genes were enriched in pathways involving cytokine‑cytokine receptor interaction and rheumatoid arthritis, whereas cytokine‑cytokine receptor interaction, cell cycle and cell adhesion molecules were the most enriched pathways in severe psoriasis group. PL1N1, TLR4, ADIPOQ, CXCL8, PDK4, CXCL1, CXCL5, LPL, AGT, LEP were hub genes in mild psoriasis, whereas BUB1, CCNB1, CCNA2, CDK1, CDH1, VEGFA, PLK1, CDC42, CCND1 and CXCL8 were reported hub genes in severe psoriasis. Among these, CDC42, for the first time (to the best of our knowledge), has been reported in the psoriasis transcriptome, with its involvement in the adaptive immune pathway. Furthermore, the immunoexpression of CDK1 and CDH1 proteins in psoriasis skin lesions were demonstrated using immunohistochemical analysis. On the whole, the findings of the present integrated bioinformatics and immunohistochemical study, may enhance our understanding of the molecular events occurring in psoriasis, and these candidate genes and pathways together may prove to be therapeutic targets for psoriasis vulgaris.

Systems Biology Approaches Reveal Potential Phenotype-Modifier Genes in Neurofibromatosis Type 1

Neurofibromatosis type (NF1) is a syndrome characterized by varied symptoms, ranging from mild to more aggressive phenotypes. The variation is not explained only by genetic and epigenetic changes in the NF1 gene and the concept of phenotype-modifier genes in extensively discussed in an attempt to explain this variability. Many datasets and tools are already available to explore the relationship between genetic variation and disease, including systems biology and expression data. To suggest potential NF1 modifier genes, we selected proteins related to NF1 phenotype and NF1 gene ontologies. Protein–protein interaction (PPI) networks were assembled, and network statistics were obtained by using forward and reverse genetics strategies. We also evaluated the heterogeneous networks comprising the phenotype ontologies selected, gene expression data, and the PPI network. Finally, the hypothesized phenotype-modifier genes were verified by a random-walk mathematical model. The network statistics analyses combined with the forward and reverse genetics strategies, and the assembly of heterogeneous networks, resulted in ten potential phenotype-modifier genes: AKT1, BRAF, EGFR, LIMK1, PAK1, PTEN, RAF1, SDC2, SMARCA4, and VCP. Mathematical models using the random-walk approach suggested SDC2 and VCP as the main candidate genes for phenotype-modifiers.

Using Micro- and Macro-Level Network Metrics Unveils Top Communicative Gene Modules in Psoriasis

(1) Background: Psoriasis is a multifactorial chronic inflammatory disorder of the skin, with significant morbidity, characterized by hyperproliferation of the epidermis. Even though psoriasis’ etiology is not fully understood, it is believed to be multifactorial, with numerous key components. (2) Methods: In order to cast light on the complex molecular interactions in psoriasis vulgaris at both protein–protein interactions and transcriptomics levels, we studied a set of microarray gene expression analyses consisting of 170 paired lesional and non-lesional samples. Afterwards, a network analysis was conducted on the protein–protein interaction network of differentially expressed genes based on micro- and macro-level network metrics at a systemic level standpoint. (3) Results: We found 17 top communicative genes, all of which were experimentally proven to be pivotal in psoriasis, which were identified in two modules, namely the cell cycle and immune system. Intra- and inter-gene interaction subnetworks from the top communicative genes might provide further insight into the corresponding characteristic interactions. (4) Conclusions: Potential gene combinations for therapeutic/diagnostics purposes were identified. Moreover, our proposed workflow could be of interest to a broader range of future biological network analysis studies.

Review-Current Concepts in Inflammatory Skin Diseases Evolved by Transcriptome Analysis: In-Depth Analysis of Atopic Dermatitis and Psoriasis

During the last decades, high-throughput assessment of gene expression in patient tissues using microarray technology or RNA-Seq took center stage in clinical research. Insights into the diversity and frequency of transcripts in healthy and diseased conditions provide valuable information on the cellular status in the respective tissues. Growing with the technique, the bioinformatic analysis toolkit reveals biologically relevant pathways which assist in understanding basic pathophysiological mechanisms. Conventional classification systems of inflammatory skin diseases rely on descriptive assessments by pathologists. In contrast to this, molecular profiling may uncover previously unknown disease classifying features. Thereby, treatments and prognostics of patients may be improved. Furthermore, disease models in basic research in comparison to the human disease can be directly validated. The aim of this article is not only to provide the reader with information on the opportunities of these techniques, but to outline potential pitfalls and technical limitations as well. Major published findings are briefly discussed to provide a broad overview on the current findings in transcriptomics in inflammatory skin diseases.

Piperlongumine regulates epigenetic modulation and alleviates psoriasis-like skin inflammation via inhibition of hyperproliferation and inflammation

Psoriasis is an autoimmune skin disease, where chronic immune responses due to exaggerated cytokine signaling, abnormal differentiation, and evasion of keratinocytes apoptosis plays a crucial role in mediating abnormal keratinocytes hyperproliferation. From the therapeutic perspective, the molecules with strong anti-proliferative and anti-inflammatory properties could have tremendous relevance. In this study, we demonstrated that piperlongumine (PPL) treatment effectively abrogated the hyperproliferation and differentiation of keratinocytes by inducing ROS-mediated late apoptosis with loss of mitochondrial membrane potential. Besides, the arrest of cell cycle was found at Sub-G1 phase as a result of DNA fragmentation. Molecularly, inhibition of STAT3 and Akt signaling was observed with a decrease in proliferative markers such as PCNA, ki67, and Cyclin D1 along with anti-apoptotic Bcl-2 protein expression. Keratin 17 is a critical regulator of keratinocyte differentiation, and it was found to be downregulated with PPL significantly. Furthermore, prominent anti-inflammatory effects were observed by inhibition of lipopolysaccharide (LPS)/Imiquimod (IMQ)-induced p65 NF-κB signaling cascade and strongly inhibited the production of cytokine storm involved in psoriasis-like skin inflammation, thus led to the restoration of normal epidermal architecture with reduction of epidermal hyperplasia and splenomegaly. In addition, PPL epigenetically inhibited histone-modifying enzymes, which include histone deacetylases (HDACs) of class I (HDAC1-4) and class II (HDAC6) evaluated by immunoblotting and HDAC enzyme assay kit. In addition, our results show that PPL effectively inhibits the nuclear translocation of p65 and a histone modulator HDAC3, thus sequestered in the cytoplasm of macrophages. Furthermore, PPL effectively enhanced the protein-protein interactions of HDAC3 and p65 with IκBα, which was disrupted by LPS stimulation and were evaluated by Co-IP and molecular modeling. Collectively, our findings indicate that piperlongumine may serve as an anti-proliferative and anti-inflammatory agent and could serve as a potential therapeutic option in treating psoriasis.

Therapeutic drug monitoring of biologics in psoriasis

Biologics are an important component of the armamentarium of drugs in the treatment of moderate to severe psoriasis. There is increasing evidence that therapeutic drug monitoring (TDM) encompassing the measurement of trough concentrations and anti-drug antibodies (ADA), together with clinical response is emerging as a valuable tool for clinical decision making. It aids in targeted dose adjustments in patients with low drug concentrations, monitoring of adherence and assessment of patients who lose response to biologics or do not respond at all. The high prevalence of psoriasis, its impact on patients' lives and costs spent on therapy motivate an evidence-based and cost-effective utility of biologics. We performed a literature review on the TDM of TNF alpha antagonists (adalimumab, infliximab, etanercept), IL12/23 antagonists (ustekinumab, guselkumab, tildrakizumab), IL17A inhibitors (secukinumab, ixekizumab) and biosimilars used in the treatment of psoriasis. Although establishing target therapeutic ranges for biologics is ideal, this has only been explored in adalimumab. We also propose a treatment algorithm for the practical application of TDM depending on drug trough concentrations, presence/absence of anti-drug antibodies and clinical response of patients. The practice of TDM is recommended in routine clinical practice where possible.

RNAI-MEDIATED SILENCING OF MATRIX METALLOPROTEINASE 1 IN EPIDERMAL KERATINOCYTES INFLUENCES THE BIOLOGICAL EFFECTS OF INTERLEUKIN 17A

Matrix metalloproteinases (MMPs) are important for the pathogenesis of psoriasis and other autoimmune disorders. In the extracellular matrix, accumulation of proinflammatory cytokines, such as interleukin 17A (IL-17A), leads to induction of several MMPs, including MMP1. MMPs change the composition and other properties of the extracellular matrix. These changes facilitate tissue remodeling and promote the development of psoriatic plaques. The aim of this study was to explore how MMP1 silencing might influence the biological effects of IL-17A on migration and proliferation of human epidermal keratinocytes and the expression of genes involved in their division and differentiation. The experiments were performed with MMP1-deficient and control epidermal keratinocytes, HaCaT-MMP1 and HaCaT-KTR, respectively. Cell proliferation and migration were assessed by comparative analysis of the growth curves and scratch assay, respectively. To quantify cell migration, representative areas of cell cultures were photographed at the indicated time points and compared to each other. Changes in gene expression were analyzed by real-time PCR. The obtained results demonstrated that MMP1 silencing in the cells treated with IL-17A resulted in downregulation of MMP9 and -12, FOSL1, CCNA2, IVL, KRT14 and -17 as well as upregulation of MMP2, CCND1 and LOR. Moreover, MMP1 silencing led to a decrease in cell proliferation and an impairment of cell migration. Thus, MMP1-deficiency in epidermal keratinocytes can be beneficial for psoriasis patients that experience an accumulation of IL-17 in lesional skin. Knocking MMP1 down could influence migration and proliferation of epidermal keratinocytes in vivo, as well as help to control the expression of MMP1, -2, -9 и -12, CCNA2, CCND1, KRT14 and -17 that are crucial for the pathogenesis of psoriasis.

Colonic Phenotypes Are Associated with Poorer Response to Anti-TNF Therapies in Patients with IBD

BACKGROUND

Although anti-tumor necrosis factor (TNF) agents are effective in patients with inflammatory bowel disease (IBD), many patients either do not respond to anti-TNF treatment or lose response over time. The aim of this study was to determine factors associated with response to anti-TNF therapy in IBD.

METHODS

Patients with Crohn's disease (CD) or ulcerative colitis who had consented to participate in a genetics registry and been treated with anti-TNF agents were evaluated retrospectively and categorized as primary nonresponders or secondary nonresponders. We evaluated clinical, serological, and genetic characteristics associated with primary nonresponse or time to loss of response to anti-TNF agents.

RESULTS

We included 314 CD (51 [16.2%] primary nonresponders and 179 [57.0%] secondary nonresponders) and 145 subjects with ulcerative colitis (43 [29.7%] primary nonresponders and 74 [51.0%] secondary nonresponders). Colonic involvement (P = 0.017; odds ratio = 8.0) and anti-TNF monotherapy (P = 0.017; odds ratio = 4.9) were associated in a multivariate analysis with primary nonresponse to anti-TNF agents in CD. In addition, higher anti-nuclear cytoplasmic antibody levels (P = 0.019; hazard ratio = 1.01) in CD, anti-nuclear cytoplasmic antibody positivity (P = 0.038; hazard ratio = 1.6) in ulcerative colitis, and a positive family history of IBD (P = 0.044; hazard ratio = 1.3) in all patients with IBD were associated with time to loss of response to anti-TNF agents. Furthermore, various known IBD susceptibility single-nucleotide polymorphisms and additional variants in immune-mediated genes were shown to be associated with primary nonresponse or time to loss of response.

CONCLUSIONS

Our results may help to optimize the use of anti-TNF agents in clinical practice and position these therapies appropriately as clinicians strive for a more personalized approach to managing IBD.

Drug Repurposing by Simulating Flow Through Protein-Protein Interaction Networks

As drug development is extremely expensive, the identification of novel indications for in‐market drugs is financially attractive. Multiple algorithms are used to support such drug repurposing, but highly reliable methods combining simulation of intracellular networks and machine learning are currently not available. We developed an algorithm that simulates drug effects on the flow of information through protein–protein interaction networks, and used support vector machine to identify potentially effective drugs in our model disease, psoriasis. Using this method, we screened about 1,500 marketed and investigational substances, identified 51 drugs that were potentially effective, and selected three of them for experimental confirmation. All drugs inhibited tumor necrosis factor alpha‐induced nuclear factor kappa B activity in vitro, suggesting they might be effective for treating psoriasis in humans. Additionally, these drugs significantly inhibited imiquimod‐induced ear thickening and inflammation in the mouse model of the disease. All results suggest high prediction performance for the algorithm.

Splicing factors differentially expressed in psoriasis alter mRNA maturation of disease-associated EDA+ fibronectin

The EDA+ fibronectin splicing variant is overexpressed in psoriatic non-lesional epidermis and sensitizes keratinocytes to mitogenic signals. However, regulation of its abundance is only partially understood. In our recent cDNA microarray experiment, we identified three SR-rich splicing factors-splicing factor, arginine/serine-rich 18 (SFRS18), peptidyl-prolyl cis-trans isomerase G (PPIG), and luc-7 like protein 3 (LUC7L3)-which might be implicated in the preactivated states of keratinocytes in psoriatic non-involved skin and could also contribute to the regulation of fibronectin mRNA maturation. In this study, we investigated the role of LUC7L3, PPIG, and SFRS18 in psoriasis and in the mRNA maturation process of fibronectin. Regarding tissue staining experiments, we were able to demonstrate a characteristic distribution of the splicing factors in healthy, psoriatic non-involved and involved epidermis. Moreover, the expression profiles of these SR-rich proteins were found to be very similar in synchronized keratinocytes. Contribution of splicing facwwtors to the EDA+ fibronectin formation was also confirmed: their siRNA silencing leads to altered fibronectin mRNA and protein expression patterns, suggesting the participation in the EDA domain inclusion. Our results indicate that LUC7L3, PPIG, and SFRS18 are not only implicated in EDA+ fibronectin formation, but also that they could possess multiple roles in psoriasis-associated molecular abnormalities.

Synthesis and activity of the salicylic acid ester of bakuchiol in psoriasis-surrogate keratinocytes and skin substitutes

BACKGROUND

Topical retinoids are effective in retarding skin ageing and restoring homeostasis in skin conditions such as psoriasis. However their adverse effects (AEs), which include irritation (retinoid dermatitis), photosensitivity and teratogenicity, limit their use and patient compliance. Development of retinoid analogues with minimal AEs would allow a broader and more compliant use.

AIM

To synthesise a novel molecule, bakuchiol salicylate (bakusylan), with a modulatory gene expression profile similar to retinoids, using as reference three prescription retinoids: tretinoin, tazarotene and adapalene.

METHODS

We hypothesized that because bakuchiol salicylate has a structure entirely different from existing retinoids, there would be at least a partial uncoupling of AEs from the skin-normalizing activity of this retinoid. This hypothesis was tested at the transcriptional level in psoriatic cytokine-treated cultures of keratinocytes and organotypic skin substitutes, using DNA microarrays and custom PCR arrays.

RESULTS

Evaluation of the gene expression profile of bakuchiol salicylate revealed elimination of several components of the retinoid-like proinflammatory response and teratogenic signature, without a substantial loss of normalizing potential. A possible mechanism of action, consisting of keratinocyte desensitization to psoriatic cytokine signalling through inhibition of the signal transducer and regulator of transcription (STAT)1/3/interferon inflammatory signal transduction axis was also identified.

CONCLUSION

Bipartite materials obtained by merging two skin-active entities with specific, complementary bioactivities, such as bakuchiol and salicylic acid, may yield a new class of functional retinoids.

Drug-target networks for Tanshinone IIA identified by data mining

Tanshinone IIA is a pharmacologically active compound isolated from Danshen (Salvia miltiorrhiza), a traditional Chinese herbal medicine for the management of cardiac diseases and other disorders. But its underlying molecular mechanisms of action are still unclear. The present investigation utilized a data mining approach based on network pharmacology to uncover the potential protein targets of Tanshinone IIA. Network pharmacology, an integrated multidisciplinary study, incorporates systems biology, network analysis, connectivity, redundancy, and pleiotropy, providing powerful new tools and insights into elucidating the fine details of drug-target interactions. In the present study, two separate drug-target networks for Tanshinone IIA were constructed using the Agilent Literature Search (ALS) and STITCH (search tool for interactions of chemicals) methods. Analysis of the ALS-constructed network revealed a target network with a scale-free topology and five top nodes (protein targets) corresponding to Fos, Jun, Src, phosphatidylinositol-4, 5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA), and mitogen-activated protein kinase kinase 1 (MAP2K1), whereas analysis of the STITCH-constructed network revealed three top nodes corresponding to cytochrome P450 3A4 (CYP3A4), cytochrome P450 A1 (CYP1A1), and nuclear factor kappa B1 (NFκB1). The discrepancies were probably due to the differences in the divergent computer mining tools and databases employed by the two methods. However, it is conceivable that all eight proteins mediate important biological functions of Tanshinone IIA, contributing to its overall drug-target network. In conclusion, the current results may assist in developing a comprehensive understanding of the molecular mechanisms and signaling pathways of in a simple, compact, and visual manner.

Graphical algorithm for integration of genetic and biological data: proof of principle using psoriasis as a model

MOTIVATION

Pathway analysis to reveal biological mechanisms for results from genetic association studies have great potential to better understand complex traits with major human disease impact. However, current approaches have not been optimized to maximize statistical power to identify enriched functions/pathways, especially when the genetic data derives from studies using platforms (e.g. Immunochip and Metabochip) customized to have pre-selected markers from previously identified top-rank loci. We present here a novel approach, called Minimum distance-based Enrichment Analysis for Genetic Association (MEAGA), with the potential to address both of these important concerns.

RESULTS

MEAGA performs enrichment analysis using graphical algorithms to identify sub-graphs among genes and measure their closeness in interaction database. It also incorporates a statistic summarizing the numbers and total distances of the sub-graphs, depicting the overlap between observed genetic signals and defined function/pathway gene-sets. MEAGA uses sampling technique to approximate empirical and multiple testing-corrected P-values. We show in simulation studies that MEAGA is more powerful compared to count-based strategies in identifying disease-associated functions/pathways, and the increase in power is influenced by the shortest distances among associated genes in the interactome. We applied MEAGA to the results of a meta-analysis of psoriasis using Immunochip datasets, and showed that associated genes are significantly enriched in immune-related functions and closer with each other in the protein-protein interaction network.

AVAILABILITY AND IMPLEMENTATION

http://genome.sph.umich.edu/wiki/MEAGA CONTACT: : tsoi.teen@gmail.com or goncalo@umich.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

What have we learned about non-involved psoriatic skin from large-scale gene expression studies?

Psoriasis is a chronic inflammatory skin disorder; its genetic background has been widely studied in recent decades. Recognition of novel factors contributing to the pathogenesis of this disorder was facilitated by potent molecular biology tools developed during the 1990s. Large-scale gene expression studies, including differential display and microarray, have been used in experimental dermatology to a great extent; moreover, skin was one of the first organs analyzed using these methods. We performed our first comprehensive gene expression analysis in 2000. With the help of differential display and microarray, we have discovered several novel factors contributing to the inherited susceptibility for psoriasis, including the EDA+ fibronectin splice variant and PRINS. The long non-coding PRINS RNA is expressed at higher levels in non-involved skin compared to healthy and involved psoriatic epidermis and might be a factor contributing cellular stress responses and, specifically, to the development of psoriatic symptoms. This review summarizes the most important results of our large-scale gene expression studies.