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综合分析探讨环境性皮肤病与环境颗粒物之间的生物学关联。

Integrative analysis to explore the biological association between environmental skin diseases and ambient particulate matter.

机构信息

Institute of Environmental Medicine, Department of Life Science, Dongguk University Biomedi Campus, 32, Dongguk-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do, 10326, Republic of Korea.

National Institute of Environmental Research, Hwangyeong-ro 42, Seo-gu, Incheon, 22689, Republic of Korea.

出版信息

Sci Rep. 2022 Jun 13;12(1):9750. doi: 10.1038/s41598-022-13001-x.

DOI:10.1038/s41598-022-13001-x
PMID:35697899
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9192598/
Abstract

Although numerous experimental studies have suggested a significant association between ambient particulate matter (PM) and respiratory damage, the etiological relationship between ambient PM and environmental skin diseases is not clearly understood. Here, we aimed to explore the association between PM and skin diseases through biological big data analysis. Differential gene expression profiles associated with PM and environmental skin diseases were retrieved from public genome databases. The co-expression among them was analyzed using a text-mining-based network analysis software. Activation/inhibition patterns from RNA-sequencing data performed with PM-treated normal human epidermal keratinocytes (NHEK) were overlapped to select key regulators of the analyzed pathways. We explored the adverse effects of PM on the skin and attempted to elucidate their relationships using public genome data. We found that changes in upstream regulators and inflammatory signaling networks mediated by MMP-1, MMP-9, PLAU, S100A9, IL-6, and S100A8 were predicted as the key pathways underlying PM-induced skin diseases. Our integrative approach using a literature-based co-expression analysis and experimental validation not only improves the reliability of prediction but also provides assistance to clarify underlying mechanisms of ambient PM-induced dermal toxicity that can be applied to screen the relationship between other chemicals and adverse effects.

摘要

尽管大量的实验研究表明，环境颗粒物（PM）与呼吸道损伤之间存在显著关联，但环境 PM 与环境性皮肤疾病之间的病因关系尚不清楚。在这里，我们旨在通过生物大数据分析来探讨 PM 与皮肤疾病之间的关联。从公共基因组数据库中检索与 PM 和环境性皮肤疾病相关的差异基因表达谱。使用基于文本挖掘的网络分析软件分析它们之间的共表达。使用 PM 处理的正常人表皮角质形成细胞（NHEK）进行 RNA-seq 数据的激活/抑制模式重叠，以选择分析途径的关键调节剂。我们探讨了 PM 对皮肤的不良影响，并尝试使用公共基因组数据阐明它们之间的关系。我们发现，由 MMP-1、MMP-9、PLAU、S100A9、IL-6 和 S100A8 介导的上游调节剂和炎症信号网络的变化被预测为 PM 诱导的皮肤疾病的关键途径。我们使用基于文献的共表达分析和实验验证的综合方法不仅提高了预测的可靠性，而且有助于阐明环境 PM 诱导的皮肤毒性的潜在机制，可用于筛选其他化学物质与不良反应之间的关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/b6d0241580ca/41598_2022_13001_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/939e4f3264c2/41598_2022_13001_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/35eb98861cac/41598_2022_13001_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/2e73acf13ab9/41598_2022_13001_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/b8bc9323a2f2/41598_2022_13001_Fig4a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/b6d0241580ca/41598_2022_13001_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/939e4f3264c2/41598_2022_13001_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/35eb98861cac/41598_2022_13001_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/2e73acf13ab9/41598_2022_13001_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/b8bc9323a2f2/41598_2022_13001_Fig4a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/9192598/b6d0241580ca/41598_2022_13001_Fig5_HTML.jpg

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