The Molecular Revolution in Cutaneous Biology: The Era of Genome-Wide Association Studies and Statistical, Big Data, and Computational Topics

Integrated analysis of immune-related long noncoding RNAs as diagnostic biomarkers in psoriasis

Background

Psoriasis is a chronic immune-mediated inflammatory dermatosis. Long noncoding RNAs (lncRNAs) play an important role in immune-related diseases. This study aimed to identify potential immune-related lncRNA biomarkers for psoriasis.

Methods

We screened differentially expressed immune-related lncRNAs biomarkers using GSE13355 (skin biopsy samples of 180 cases) from Gene Expression Omnibus (GEO). Moreover, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Set Enrichment Analysis (GSEA) were performed to explore biological mechanisms in psoriasis. In addition, we performed LASSO logistic regression to identify potential diagnostic lncRNAs and further verify the diagnostic value and relationship with drug response using two validation sets: GSE30999 (skin biopsy samples of 170 cases) and GSE106992 (skin biopsy samples of 192 cases). Furthermore, we estimated the degree of infiltrated immune cells and investigated the correlation between infiltrated immune cells and diagnostic lncRNA biomarkers.

Results

A total of 394 differentially expressed genes (DEGs) were extracted from gene expression profile. GO and KEGG analysis of target genes found that immune-related lncRNAs were primarily associated with epidermis development, skin development, collagen-containing extracellular matrix, and glycosaminoglycan binding and mainly enriched in cytokine-cytokine receptor interaction and influenza A and chemokine signaling pathway. We found that LINC01137, LINC01215, MAPKAPK5-AS1, TPT1-AS1, CARMN, CCDC18-AS1, EPB41L4A-AS, and LINC01214 exhibited well diagnostic efficacy. The ROC and ROC CI were 0.944 (0.907–0.982), 0.953 (0.919–0.987), 0.822 (0.758–0.887), 0.854 (0.797–0.911), 0.957(0.929–0.985), 0.894 (0.846–0.942), and 0.964 (0.937–0.991) for LINC01137, LINC01215, MAPKAPK5-AS1, TPT1-AS1,CARMN, CCDC18-AS1, EPB41L4A-AS1, and LINC01214. LINC01137, LINC01215, and LINC01214 were correlated with drug response. LINC01137, CCDC18-AS1, and CARMN were positively correlated with activated memory CD4 T cell, activated myeloid dendritic cell (DC), neutrophils, macrophage M1, and T follicular helper (Tfh) cells, while negatively correlated with T regulatory cell (Treg). LINC01215, MAPKAPK5-AS1, TPT1-AS1, EPB41L4A-AS, and LINC01214 were negatively correlated with activated memory CD4 T cell, activated myeloid DC, neutrophils, macrophage M1, and Tfh, while positively correlated with Treg.

Conclusions

These findings indicated that these immune-related lncRNAs may be used as potential diagnostic and predictive biomarkers for psoriasis.

Psoriasis: Association of interleukin-17 gene polymorphisms with severity and response to treatment

Psoriasis is a chronic, inflammatory disease with a complex pathogenesis that is not yet fully understood. Although it is a multifactorial disease, the genetic factor has a major role in the pathogenesis of psoriasis. Genome wide association studies have identified over 50 genetic loci associated with psoriasis risk. Beside TNF-α or IL-23, the IL-17 family is a newer group that has proven implications in the pathogenesis of psoriasis. The most important members of the family, with pro-inflammatory qualities, are IL-17A and IL-17F. These interleukins are produced by a varied number of cells, but by far the most important are Th17 cells. Of the patients 20-30% present moderate-to-severe psoriasis, therefore, systemic medication (phototherapy, methotrexate, cyclosporine, acitretin or biologic agents) is mandatory. The necessity of an individualized treatment plan, for each patient, is imperative in order to establish the best strategy for non-responders to classical treatment or to other biologic treatments. The discovery of Th17 pathway improved the treatment and prognosis of psoriasis. Anti-psoriatic agents against IL-17 or its receptors are a novel group of biologic agents; these include ixekizumab, secukinumab and brodalumab. Polymorphisms of IL-17 family have been correlated with the severity and response to treatment in psoriasis, and also with the risk of inflammatory, infectious, autoimmune or neoplastic pathologies. The significant difference in the presence or absence of susceptibility loci in different population is due to genetic background and environmental factors that have a major impact on disease predisposition. In this study, we reviewed the importance and influence of the IL-17 polymorphisms as predictors of response to treatment and severity of the disease.

Genetics of psoriasis: a basis for precision medicine

Psoriasis is an inflammatory skin disease with a background of polygenic inheritance. Both environmental and genetic factors are involved in the etiology of the disease. In the last two decades, numerous studies have been conducted through linkage analysis, genome-wide association study (GWAS), and direct sequencing to explore the role of genetic variation in disease pathogenesis and progression. To date, >80 psoriasis susceptibility genes have been identified, including HLA-Cw6, IL12B, IL23R, and LCE3B/3C. Some genetic markers have been applied in disease prediction, clinical diagnosis, treatment, and new drug development, which could further explain the pathogenesis of psoriasis and promote the development of precision medicine. This review summarizes related research on genetic variation in psoriasis and explores implications of the findings in clinical application and the promotion of a personalized medicine project.

The epithelial immune microenvironment (EIME) in atopic dermatitis and psoriasis

The skin provides both a physical barrier and an immunologic barrier to external threats. The protective machinery of the skin has evolved to provide situation-specific responses to eliminate pathogens and to provide protection against physical dangers. Dysregulation of this machinery can give rise to the initiation and propagation of inflammatory loops in the epithelial microenvironment that result in inflammatory skin diseases in susceptible people. A defective barrier and microbial dysbiosis drive an interleukin 4 (IL-4) loop that underlies atopic dermatitis, while in psoriasis, disordered keratinocyte signaling and predisposition to type 17 responses drive a pathogenic IL-17 loop. Here we discuss the pathogenesis of atopic dermatitis and psoriasis in terms of the epithelial immune microenvironment-the microbiota, keratinocytes and sensory nerves-and the resulting inflammatory loops.

Discovering Genetic Factors for psoriasis through exhaustively searching for significant second order SNP-SNP interactions

In this paper, we aim at discovering genetic factors of psoriasis through searching for statistically significant SNP-SNP interactions exhaustively from two real psoriasis genome-wide association study datasets (phs000019.v1.p1 and phs000982.v1.p1) downloaded from the database of Genotypes and Phenotypes. To deal with the enormous search space, our search algorithm is accelerated with eight biological plausible interaction patterns and a pre-computed look-up table. After our search, we have discovered several SNPs having a stronger association to psoriasis when they are in combination with another SNP and these combinations may be non-linear interactions. Among the top 20 SNP-SNP interactions being found in terms of pairwise p-value and improvement metric value, we have discovered 27 novel potential psoriasis-associated SNPs where most of them are reported to be eQTLs of a number of known psoriasis-associated genes. On the other hand, we have inferred a gene network after selecting the top 10000 SNP-SNP interactions in terms of improvement metric value and we have discovered a novel long distance interaction between XXbac-BPG154L12.4 and RNU6-283P which is not a long distance haplotype and may be a new discovery. Finally, our experiments with the synthetic datasets have shown that our pre-computed look-up table technique can significantly speed up the search process.

The convergence theory for vitiligo: A reappraisal

Vitiligo is characterized by progressive loss of skin pigmentation. The search for aetiologic factors has led to the biochemical, the neurologic and the autoimmune theory. The convergence theory was then proposed several years ago to incorporate existing theories of vitiligo development into a single overview of vitiligo aetiology. The viewpoint that vitiligo is not caused only by predisposing mutations, or only by melanocytes responding to chemical/radiation exposure, or only by hyperreactive T cells, but rather results from a combination of aetiologic factors that impact melanocyte viability, has certainly stood the test of time. New findings have since informed the description of progressive depigmentation. Understanding the relative importance of such aetiologic factors combined with a careful selection of the most targetable pathways will continue to drive the next phase in vitiligo research: the development of effective therapeutics. In that arena, it is likewise important to acknowledge that pathways affected in some patients may not be altered in others. Taken together, the convergence theory continues to provide a comprehensive viewpoint of vitiligo aetiology. The theory serves to intertwine aetiologic pathways and will help to define pathways amenable to disease intervention in individual patients.

Atopic dermatitis

Atopic dermatitis (AD) is the most common chronic inflammatory skin disease, with a lifetime prevalence of up to 20% and substantial effects on quality of life. AD is characterized by intense itch, recurrent eczematous lesions and a fluctuating course. AD has a strong heritability component and is closely related to and commonly co-occurs with other atopic diseases (such as asthma and allergic rhinitis). Several pathophysiological mechanisms contribute to AD aetiology and clinical manifestations. Impairment of epidermal barrier function, for example, owing to deficiency in the structural protein filaggrin, can promote inflammation and T cell infiltration. The immune response in AD is skewed towards T helper 2 cell-mediated pathways and can in turn favour epidermal barrier disruption. Other contributing factors to AD onset include dysbiosis of the skin microbiota (in particular overgrowth of Staphylococcus aureus), systemic immune responses (including immunoglobulin E (IgE)-mediated sensitization) and neuroinflammation, which is involved in itch. Current treatments for AD include topical moisturizers and anti-inflammatory agents (such as corticosteroids, calcineurin inhibitors and cAMP-specific 3',5'-cyclic phosphodiesterase 4 (PDE4) inhibitors), phototherapy and systemic immunosuppressants. Translational research has fostered the development of targeted small molecules and biologic therapies, especially for moderate-to-severe disease.

Research Techniques Made Simple: Bioinformatics for Genome-Scale Biology

High-throughput biology presents unique opportunities and challenges for dermatological research. Drawing on a small handful of exemplary studies, we review some of the major lessons of these new technologies. We caution against several common errors and introduce helpful statistical concepts that may be unfamiliar to researchers without experience in bioinformatics. We recommend specific software tools that can aid dermatologists at varying levels of computational literacy, including platforms with command line and graphical user interfaces. The future of dermatology lies in integrative research, in which clinicians, laboratory scientists, and data analysts come together to plan, execute, and publish their work in open forums that promote critical discussion and reproducibility. In this article, we offer guidelines that we hope will steer researchers toward best practices for this new and dynamic era of data intensive dermatology.