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Biogeographic and disease-specific alterations in epidermal lipid composition and single-cell analysis of acral keratinocytes
Alexander A. Merleev, … , Johann E. Gudjonsson, Emanual Maverakis
Alexander A. Merleev, … , Johann E. Gudjonsson, Emanual Maverakis
Published July 28, 2022
Citation Information: JCI Insight. 2022;7(16):e159762. https://doi.org/10.1172/jci.insight.159762.
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Resource and Technical Advance Dermatology

Biogeographic and disease-specific alterations in epidermal lipid composition and single-cell analysis of acral keratinocytes

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Abstract

The epidermis is the outermost layer of skin. Here, we used targeted lipid profiling to characterize the biogeographic alterations of human epidermal lipids across 12 anatomically distinct body sites, and we used single-cell RNA-Seq to compare keratinocyte gene expression at acral and nonacral sites. We demonstrate that acral skin has low expression of EOS acyl-ceramides and the genes involved in their synthesis, as well as low expression of genes involved in filaggrin and keratin citrullination (PADI1 and PADI3) and corneodesmosome degradation, changes that are consistent with increased corneocyte retention. Several overarching principles governing epidermal lipid expression were also noted. For example, there was a strong negative correlation between the expression of 18-carbon and 22-carbon sphingoid base ceramides. Disease-specific alterations in epidermal lipid gene expression and their corresponding alterations to the epidermal lipidome were characterized. Lipid biomarkers with diagnostic utility for inflammatory and precancerous conditions were identified, and a 2-analyte diagnostic model of psoriasis was constructed using a step-forward algorithm. Finally, gene coexpression analysis revealed a strong connection between lipid and immune gene expression. This work highlights (a) mechanisms by which the epidermis is uniquely adapted for the specific environmental insults encountered at different body surfaces and (b) how inflammation-associated alterations in gene expression affect the epidermal lipidome.

Authors

Alexander A. Merleev, Stephanie T. Le, Claire Alexanian, Atrin Toussi, Yixuan Xie, Alina I. Marusina, Steven M. Watkins, Forum Patel, Allison C. Billi, Julie Wiedemann, Yoshihiro Izumiya, Ashish Kumar, Ranjitha Uppala, J. Michelle Kahlenberg, Fu-Tong Liu, Iannis E. Adamopoulos, Elizabeth A. Wang, Chelsea Ma, Michelle Y. Cheng, Halani Xiong, Amanda Kirane, Guillaume Luxardi, Bogi Andersen, Lam C. Tsoi, Carlito B. Lebrilla, Johann E. Gudjonsson, Emanual Maverakis

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Figure 14

Altered ELOVL4 expression impacts expression of immune genes in keratinocytes.

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Altered ELOVL4 expression impacts expression of immune genes in keratino...
(A) RNA-Seq data sets of psoriasis lesional skin were mined for gene expression of ELOVL4, IL36B, PDE4A, CHMP2B, CDK7, and S100A13. These genes were selected because they were highly coexpressed with ELOVL4 in primary human keratinocytes and are known inflammatory mediators that are differentially expressed in psoriasis lesional skin. A metaanalysis was performed to combine the ELOVL4 coexpression results across 4 independently acquired RNA-Seq data sets. Forest plots are presented, and P values for the final model are shown. (B) Keratinocyte RNA-Seq data sets were parsed into 3 groups based on the ELOVL4 allele they expressed (0/0 representing the ELOVL4 reference allele, and 0/1 and 1/1 representing heterozygosity and homozygosity for the ELOVL4 variant, rs62407622). Box plots of ELOVL4 expression revealed that keratinocytes homozygous for rs62407622 expressed significantly reduced levels of ELOVL4. Keratinocytes homozygous for the ELOVL4lo variant also expressed significantly lower levels of CDK7, CHMP2B, IL36B, and MAP3K8 and significantly increased levels of PDE4A, S100A13, and TLR3. (C) HaCat and N/TERT immortalized keratinocyte cell lines were treated with ELOVL4 siRNA or control scrambled RNA. ELOVL4 siRNA knockdown significantly downregulated expression of CDK7, CHMP2B, DNAJA2, and MAP3K8. It also increased expression of PDE4A in N/TERT cells and TLR3 in HaCaT cells. (D) ELOVL4 coexpression network. Line thickness is directly proportional the correlation coefficient for the coexpression of the connecting genes. Red lines indicate a positive correlation, and blue lines indicate a negative correlation.

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