Non-invasive acquisition of mRNA data from the skin can be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable levels of human mRNAs exist in SSLs, where the sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNA levels, and our results revealed that the SSL-RNAs predominantly comprised mRNAs derived from sebaceous glands, the epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed increased expression of inflammation-related genes and decreased expression of terminal differentiation-related genes, consistent with the results of previous reports. Further, we found that lipid synthesis-related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is a promising strategy to understand the pathophysiology of skin diseases.
Parkinson's disease (PD) is a progressive neurodegenerative disease presenting with motor and non-motor symptoms, including skin disorders (seborrheic dermatitis, bullous pemphigoid, and rosacea), skin pathological changes (decreased nerve endings and alpha-synuclein deposition), and metabolic changes of sebum. Recently, a transcriptome method using RNA in skin surface lipids (SSL-RNAs) which can be obtained non-invasively with an oil-blotting film was reported as a novel analytic method of sebum. Here we report transcriptome analyses using SSL-RNAs and the potential of these expression profiles with machine learning as diagnostic biomarkers for PD in double cohorts (PD [n = 15, 50], controls [n = 15, 50]). Differential expression analysis between the patients with PD and healthy controls identified more than 100 differentially expressed genes in the two cohorts. In each cohort, several genes related to oxidative phosphorylation were upregulated, and gene ontology analysis using differentially expressed genes revealed functional processes associated with PD. Furthermore, machine learning using the expression information obtained from the SSL-RNAs was able to efficiently discriminate patients with PD from healthy controls, with an area under the receiver operating characteristic curve of 0.806. This non-invasive gene expression profile of SSL-RNAs may contribute to early PD diagnosis based on the neurodegeneration background.
Non-invasive acquisition of mRNA data from the skin would be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable human mRNAs exist in SSLs, where sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNAs, and our results revealed that SSL-RNAs predominantly contained mRNAs derived from sebaceous glands, epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed significantly increased expression of inflammation-related genes and decreased expression of terminal differentiation-related genes, consistent with the results of previous reports. Further, we found that lipid synthesis-related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is promising to understand the pathophysiology of skin diseases.
Background Specimens for analysing the molecular pathology of skin disease are generally obtained through invasive methods, such as biopsy. However, less burdensome methods are desirable for paediatric patients. We recently established a method that comprehensively analyses RNA present in sebum (skin surface lipid–RNAs: SSL‐RNAs) using a next‐generation sequencer. Using this method, biological information can be obtained from the skin in a completely non‐invasive manner. Objectives To verify the applicability of the SSL‐RNA method for analysis of paediatric skin and analyse the molecular pathology of mild‐to‐moderate atopic dermatitis (AD) in children. Methods We collected sebum specimens from the whole faces of 23 healthy children and 16 children with mild‐to‐moderate AD (eczema area and severity index (EASI) score: 5.9 ± 2.6) ranging in age from 6 months to 5 years, using an oil‐blotting film. We then extracted SSL‐RNAs from the samples and performed an AmpliSeq transcriptomic analysis. Results The expressions of genes related to keratinization (LCE, PSORS1C2, IVL and KRT17), triglyceride synthesis and storage (PLIN2, DGAT2 and CIDEA), wax synthesis (FAR2), ceramide synthesis (GBA2, SMPD3 and SPTLC3), antimicrobial peptides (DEFB1) and intercellular adhesion (CDSN), all of which are related to the skin barrier, are lower in children with AD than in healthy children. The children with AD also have higher expression of CCL17, a Th2‐cytokine and an increased Th2‐immune response as demonstrated by a gene set variation analysis. Moreover, KRT17 and CCL17 expression levels are significantly correlated with the EASI score. Conclusions Molecular changes associated with abnormal immune responses and the epidermal barrier in children with mild‐to‐moderate AD can be determined using the SSL‐RNA method. This non‐invasive method could therefore be a useful means for understanding the molecular pathology of paediatric AD.
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