Cargando…

SG-APSIC1087: Transcriptome meta-analysis revealed concordant molecular signatures between acne skin and PM2.5-treated in vitro skin models

Objectives: Cohort and epidemiology studies have previously revealed potential associations between air pollution exposure and acne vulgaris. However, the molecular mechanisms that drive these associations are not currently well understood. In this study, we compared the molecular signatures of acne...

Descripción completa

Detalles Bibliográficos
Autores principales: Gu, Xuelan, Cui, Xiao, Zhang, Hong, Mi, Grace
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571126/
http://dx.doi.org/10.1017/ash.2023.41
_version_ 1785119915625152512
author Gu, Xuelan
Cui, Xiao
Zhang, Hong
Mi, Grace
author_facet Gu, Xuelan
Cui, Xiao
Zhang, Hong
Mi, Grace
author_sort Gu, Xuelan
collection PubMed
description Objectives: Cohort and epidemiology studies have previously revealed potential associations between air pollution exposure and acne vulgaris. However, the molecular mechanisms that drive these associations are not currently well understood. In this study, we compared the molecular signatures of acne and PM2.5-exposed skin to infer whether common underlying biological mechanisms exist. Methods: Acne microarray data sets were downloaded from GEO. RMAExpress was used for microarray normalization, and TMeV was used to identify differential expressed genes (DEGs). A random-effects model in MetaVolcanoR was used to determine fold changes and P values. DEGs of PM2.5-exposed skin-cell models were obtained from the literature. DEGs were compared using GeneOverlap and a custom R script. Analyses of pathways, upstream regulators, and causal networks were conducted using ingenuity pathway analysis (IPA). Results: The molecular signatures of acne skin and the effect of PM2.5 on skin in vitro were compared at 3 levels: (1) gene expression, (2) pathway activity, and (3) upstream regulators. Significant concordant overlaps of both upregulated (P < 3e-23) and downregulated DEGs (P< .005) were observed in acne skin and PM2.5-exposed keratinocytes. However, for the PM2.5-exposed 3D skin model, significant overlap with acne skin was only observed for upregulated DEGs (P < 8e-14). Fold changes of DEGs in both acne and PM2.5-exposed data sets showed significant correlation (Pearson correlation coefficient > 0.6; P < .001). An IPA analysis identified 13 pathways commonly enriched in acne and PM2.5 data sets, including IL17, IL6, Toll receptor PPAR, LXR–RXR, and acute-phase response pathways. Common upstream regulators were further identified including TNFα, NFκB, CAMP, AhR, and IL17A. Finally, causal network analysis revealed several potential hub regulators shared in acne pathogenesis and PM2.5-exposed skin, including HIF1α, TNF, IL1α, and CCL5. Conclusions: Our analysis revealed significant concordant molecular signatures between acne and PM2.5-exposed skin. Biological insights from this study offer clues that build the causal links between air pollution and acne pathogenesis.
format Online
Article
Text
id pubmed-10571126
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Cambridge University Press
record_format MEDLINE/PubMed
spelling pubmed-105711262023-10-14 SG-APSIC1087: Transcriptome meta-analysis revealed concordant molecular signatures between acne skin and PM2.5-treated in vitro skin models Gu, Xuelan Cui, Xiao Zhang, Hong Mi, Grace Antimicrob Steward Healthc Epidemiol Environmental Hygiene Objectives: Cohort and epidemiology studies have previously revealed potential associations between air pollution exposure and acne vulgaris. However, the molecular mechanisms that drive these associations are not currently well understood. In this study, we compared the molecular signatures of acne and PM2.5-exposed skin to infer whether common underlying biological mechanisms exist. Methods: Acne microarray data sets were downloaded from GEO. RMAExpress was used for microarray normalization, and TMeV was used to identify differential expressed genes (DEGs). A random-effects model in MetaVolcanoR was used to determine fold changes and P values. DEGs of PM2.5-exposed skin-cell models were obtained from the literature. DEGs were compared using GeneOverlap and a custom R script. Analyses of pathways, upstream regulators, and causal networks were conducted using ingenuity pathway analysis (IPA). Results: The molecular signatures of acne skin and the effect of PM2.5 on skin in vitro were compared at 3 levels: (1) gene expression, (2) pathway activity, and (3) upstream regulators. Significant concordant overlaps of both upregulated (P < 3e-23) and downregulated DEGs (P< .005) were observed in acne skin and PM2.5-exposed keratinocytes. However, for the PM2.5-exposed 3D skin model, significant overlap with acne skin was only observed for upregulated DEGs (P < 8e-14). Fold changes of DEGs in both acne and PM2.5-exposed data sets showed significant correlation (Pearson correlation coefficient > 0.6; P < .001). An IPA analysis identified 13 pathways commonly enriched in acne and PM2.5 data sets, including IL17, IL6, Toll receptor PPAR, LXR–RXR, and acute-phase response pathways. Common upstream regulators were further identified including TNFα, NFκB, CAMP, AhR, and IL17A. Finally, causal network analysis revealed several potential hub regulators shared in acne pathogenesis and PM2.5-exposed skin, including HIF1α, TNF, IL1α, and CCL5. Conclusions: Our analysis revealed significant concordant molecular signatures between acne and PM2.5-exposed skin. Biological insights from this study offer clues that build the causal links between air pollution and acne pathogenesis. Cambridge University Press 2023-03-16 /pmc/articles/PMC10571126/ http://dx.doi.org/10.1017/ash.2023.41 Text en © The Society for Healthcare Epidemiology of America 2023 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Environmental Hygiene
Gu, Xuelan
Cui, Xiao
Zhang, Hong
Mi, Grace
SG-APSIC1087: Transcriptome meta-analysis revealed concordant molecular signatures between acne skin and PM2.5-treated in vitro skin models
title SG-APSIC1087: Transcriptome meta-analysis revealed concordant molecular signatures between acne skin and PM2.5-treated in vitro skin models
title_full SG-APSIC1087: Transcriptome meta-analysis revealed concordant molecular signatures between acne skin and PM2.5-treated in vitro skin models
title_fullStr SG-APSIC1087: Transcriptome meta-analysis revealed concordant molecular signatures between acne skin and PM2.5-treated in vitro skin models
title_full_unstemmed SG-APSIC1087: Transcriptome meta-analysis revealed concordant molecular signatures between acne skin and PM2.5-treated in vitro skin models
title_short SG-APSIC1087: Transcriptome meta-analysis revealed concordant molecular signatures between acne skin and PM2.5-treated in vitro skin models
title_sort sg-apsic1087: transcriptome meta-analysis revealed concordant molecular signatures between acne skin and pm2.5-treated in vitro skin models
topic Environmental Hygiene
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571126/
http://dx.doi.org/10.1017/ash.2023.41
work_keys_str_mv AT guxuelan sgapsic1087transcriptomemetaanalysisrevealedconcordantmolecularsignaturesbetweenacneskinandpm25treatedinvitroskinmodels
AT cuixiao sgapsic1087transcriptomemetaanalysisrevealedconcordantmolecularsignaturesbetweenacneskinandpm25treatedinvitroskinmodels
AT zhanghong sgapsic1087transcriptomemetaanalysisrevealedconcordantmolecularsignaturesbetweenacneskinandpm25treatedinvitroskinmodels
AT migrace sgapsic1087transcriptomemetaanalysisrevealedconcordantmolecularsignaturesbetweenacneskinandpm25treatedinvitroskinmodels