Atopic dermatitis and skin disease
RNA sequencing atopic dermatitis transcriptome profiling provides insights into novel disease mechanisms with potential therapeutic implications

https://doi.org/10.1016/j.jaci.2015.03.003Get rights and content

Background

Genomic profiling of lesional and nonlesional skin of patients with atopic dermatitis (AD) using microarrays has led to increased understanding of AD and identification of novel therapeutic targets. However, the limitations of microarrays might decrease detection of AD genes. These limitations might be lessened with next-generation RNA sequencing (RNA-seq).

Objective

We sought to define the lesional AD transcriptome using RNA-seq and compare it using microarrays performed on the same cohort.

Methods

RNA-seq and microarrays were performed to identify differentially expressed genes (criteria: fold change, ≥2.0; false discovery rate ≤0.05) in lesional versus nonlesional skin from 18 patients with moderate-to-severe AD, with real-time PCR (RT-PCR) and immunohistochemistry used for validation.

Results

Both platforms showed robust disease transcriptomes and correlated well with RT-PCR. The common AD transcriptome identified by using both techniques contained 217 genes, including inflammatory (S100A8/A9/A12, CXCL1, and 2′-5′-oligoadenylate synthetase-like [OASL]) and barrier (MKi67, keratin 16 [K16], and claudin 8 [CLDN8]) AD-related genes. Although fold change estimates determined by using RNA-seq showed somewhat better agreement with RT-PCR (intraclass correlation coefficient, 0.57 and 0.70 for microarrays and RNA-seq vs RT-PCR, respectively), bias was not eliminated. Among genes uniquely identified by using RNA-seq were triggering receptor expressed on myeloid cells 1 (TREM-1) signaling (eg, CCL2, CCL3, and single immunoglobulin domain IL1R1 related [SIGIRR]) and IL-36 isoform genes. TREM-1 is a surface receptor implicated in innate and adaptive immunity that amplifies infection-related inflammation.

Conclusions

This is the first report of a lesional AD phenotype using RNA-seq and the first direct comparison between platforms in this disease. Both platforms robustly characterize the AD transcriptome. Through RNA-seq, we unraveled novel disease pathology, including increased expression of the novel TREM-1 pathway and the IL-36 cytokine in patients with AD.

Section snippets

Patients and samples

Biopsy specimens of lesional and nonlesional skin were collected from 20 consented patients with moderate-to-severe AD included in our cyclosporin A (CsA) study (see Table E1 in this article's Online Repository at www.jacionline.org).13 Sera from 8 healthy subjects (4 male and 4 female subjects; age, 26-57 years [median, 32 years]) were collected for comparison of soluble triggering receptor expressed on myeloid cells 1 (TREM-1) levels (see Table E1).

RT-PCR and microarrays

RT-PCR was performed on 34 preselected

Results

In this study we used the same cohort of patients with moderate-to-severe AD treated with CsA13, 19 for whom genomic profiles were simultaneously obtained with Affymetrix Human Genome U133APlus 2.0 (GSE#58558) and RNA-seq by using Illumina HiSeq2500 (100 cycles, single-read sequencing, 4 samples per lane). RT-PCR on 34 preselected AD genes served for comparison (Fig 1). Two patients were excluded after quality control. Thus the analysis cohort for microarray and RNA-seq analyses included 18

Discussion

Genomic skin profiling has gained acceptance as a sensitive tool to measure early disease improvement in patients with psoriasis36, 37, 38 and, lately, also in AD clinical trials of emerging therapeutics.3, 13, 16 These studies primarily use microarrays to define relevant disease transcriptomes, with good correlations between the clinical disease improvements (by Psoriasis Area and Severity Index36, 38 and SCORAD or Eczema Area and Severity Index scores)13, 14, 16 and the molecular changes in

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    Supported in part by grant no. UL1 TR000043 from the National Center for Advancing Translational Sciences (NCATS), a National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) program. Also supported by a research grant to E.G.-Y. from Bristol-Myers Squibb. D.A.E is a joint PhD student of Leo Pharma and DTU and partly funded by the Danish Ministry of Higher Education and Science.

    Disclosure of potential conflict of interest: This study was funded by Bristol-Myers Squibb and the National Institutes of Health. D. A. Ewald is employed by LEO Pharma AS and has received or has grants pending from the Danish Ministry of Higher Education and Science. S. R. Dillon is employed by ZymoGenetics and holds stock options in this Bristol-Myers Squibb. J. G. Krueger's institution has received funding from Novartis, Pfizer, Amgen, Lilly, Merck, Kadmon, Dermira, Boehringer, Innovaderm, Kyowa, Bristol-Myers Squibb, Serono, Jamssen, Paraxel, and he has received personal fees from Serono, Biogen Idec, Delenex, AbbVie, Sanofi, Baxter, Xenoport, and Kineta. E. Guttman-Yassky has received compensation for board membership from Sanofi Aventis, Regeneron, Stiefel/GlaxoSmithKline, Medimmune, Celgene, Anacor, and Leo Pharma, as well as consultancy fees from Regeneron, Sanofi Aventis, Medimmune, Celgene, Stiefel/GlaxoSmithKline, Celsus, BMS, Amgen, and Drais; and her institution has received or has grants pending from Regeneron, Celgene, BMS, and Janssen. The rest of the authors declare that they have no relevant conflicts of interest.

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