Long noncoding RNAs (lncRNAs) regulate the expression of protein-coding genes and have been shown to play important roles in inflammatory skin diseases. However, we still have limited understanding of the functional impact of lncRNAs in skin, partly due to their tissue specificity and lower expression levels compared with protein-coding genes. We compiled a comprehensive list of 18,517 lncRNAs from different sources and studied their expression profiles in 834 RNA-Seq samples from multiple inflammatory skin conditions and cytokine-stimulated keratinocytes. Applying a balanced random forest to predict involvement in biological functions, we achieved a median AUROC of 0.79 in 10-fold cross-validation, identifying significant DNA binding domains (DBDs) for 39 lncRNAs. G18244, a skin-expressing lncRNA predicted for IL-4/IL-13 signaling in keratinocytes, was highly correlated in expression with F13A1, a protein-coding gene involved in macrophage regulation, and we further identified a significant DBD in F13A1 for G18244. Reflecting clinical implications, AC090198.1 (predicted for IL-17 pathway) and AC005332.6 (predicted for IFN-γ pathway) had significant negative correlation with the SCORAD metric for atopic dermatitis. We also utilized single-cell RNA and spatial sequencing data to validate cell type specificity. Our research demonstrates lncRNAs have important immunological roles and can help prioritize their impact on inflammatory skin diseases.
Matthew T. Patrick, Sutharzan Sreeskandarajan, Alanna Shefler, Rachael Wasikowski, Mrinal K. Sarkar, Jiahan Chen, Tingting Qin, Allison C. Billi, J. Michelle Kahlenberg, Errol Prens, Alain Hovnanian, Stephan Weidinger, James T. Elder, Chao-Chung Kuo, Johann E. Gudjonsson, Lam C. Tsoi
Usage data is cumulative from December 2023 through August 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 1,140 | 230 |
210 | 32 | |
Figure | 192 | 0 |
Table | 50 | 0 |
Supplemental data | 100 | 5 |
Citation downloads | 41 | 0 |
Totals | 1,733 | 267 |
Total Views | 2,000 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.