Multiple Transcriptome Data Analysis Reveals Biologically Relevant Atopic Dermatitis Signature Genes and Pathways

<div><p>Several studies have identified genes that are differentially expressed in atopic dermatitis (AD) compared to normal skin. However, there is also considerable variation in the list of differentially expressed genes (DEGs) reported by different groups and the exact cause of AD is still not fully understood. Using a rank-based approach, we analyzed gene expression data from five different microarray studies, comprising a total of 127 samples and more than 250,000 transcripts. A total of 89 AD gene expression signatures ‘89ADGES’, including <i>FLG</i> gene, were identified to show <i>dysregulation</i> consistently across these studies. Using a Support Vector Machine, we showed that the ‘89ADGES’ discriminates AD from normal skin with 98% predictive accuracy. Functional annotation of these genes implicated their roles in immune responses (e.g., betadefensin, microseminoprotein), keratinocyte differentiation/epidermal development (e.g., <i>FLG</i>, <i>CORIN</i>, <i>AQP</i>, <i>LOR</i>, <i>KRT16</i>), inflammation (e.g., <i>IL37</i>, <i>IL27RA</i>, <i>CCL18</i>) and lipid metabolism (e.g., <i>AKR1B10</i>, <i>FAD7</i>, <i>FAR2</i>). Subsequently, we validated a subset of signature genes using quantitative PCR in a mouse model. Using a bioinformatic approach, we identified keratinocyte pathway over-represented (P = <0.0006) among the 89 signature genes. Keratinocytes are known to play a major role in barrier function due to their location in the epidermis. Our result suggests that besides immune- mediated pathway, skin barrier pathways such as the keratinocyte differentiation pathway play a key role in AD pathogenesis. A better understanding of the role of keratinocytes in AD will be important for developing novel “barrier therapy” for this disease.</p></div

Analysis of the ‘89ADEGs’ with the ACUMENTA literature lab demonstrated an enriched of the keratinocyte differentiation pathway.

<p>Keratinocytes are known to play a major role in barrier function in AD due to their location in the epidermis. DEGs associated with the keratinocyte differentiation pathway have been shown. The biological functions of these genes were related to cellular movement, barrier functions, signaling as well as cellular development and function. The genes making the strongest contribution are shown in the inner ring starting at the 12 o’clock position and descending in a clockwise direction and outward in the order of contribution to the association to keratinocyte differentiation pathway. Thus <i>LOR</i> accounts for the largest share of the gene set's association with the keratinocyte differentiation pathway, followed by <i>FLG</i> then <i>KRT16</i> and so on. The gene in this diagram contributing the least to the gene set's association with the keratinocyte differentiation pathway is <i>AOP9</i>.</p

Major steps in the analysis of transcriptome data.

<p>Five individual datasets, obtained from GEO, were first normalized and quality-checked using hierarchical cluster analysis (HCA) and principal component analysis (PCA), and differentially expressed genes (DEGs; fold change ≥ 1.5) were identified from each dataset. Genes differentially regulated between AD and non-AD controls in at least 3 out of 5 datasets (common dataset ratio ≥ 0.6), were ranked by fold-change. Ingenuity Pathway Analysis (IPA) were conducted for network analysis and ACUMENTA for pathway analysis, and Support Vector Machine and discriminant analysis were used to discriminate and predict membership of AD patients from healthy controls.</p

DEGs classified by functions.

<p>A, Barrier function; B, protease-protease inhibitor homeostasis; C, anti-microbial response genes; D, cytokine/ chemokine/ growth factor; E, lipid genes, and F, genes with diverse metabolic functions. Color codes: white, no expression data for that particular gene exist in the GEO dataset; red, up-regulated; green, down-regulated in AD.</p

Top biological networks identified using IPA connecting several DEGs for (a) lesional and non-lesional combined (b) lesional (c) non-lesional AD.

<p>Lipid genes, protease genes and immune-related ‘nodal genes’, controlling several DEGs, are located at the center of the networks. Solid lines represent direct and established regulatory functions, while dotted lines represent indirect roles.</p

Distribution of fold change and average percent significance rank of 89ADEGS.

<p>Identification and ranking of differentially expressed genes (DEGs) from individual studies using both ranked statistical significance (x-axis) and biological relevance (fold change, FC, y-axis) provide better understanding of relevant gene sets than either of the methods. The p-values of the 89ADGES member genes were arranged (smaller to larger p-values) in each of the datasets and percent-ranked. For example, the percent-rank of a DEG/transcript at the 500^th position within a set of 50,000 transcript will rank 5^th. Average percent ranks each 89ADGES member gene was determined by averaging the percent-ranks from 5 datasets and plotted against respective average fold-change values. A lower percent rank indicates higher significance (Please see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144316#pone.0144316.s005" target="_blank">S2 Table</a> for details). Upregulated genes are in red color.</p