Human Skin Responses to Environmental Pollutants: A Review of Current Scientific Models

Whatever the exposure route, chemical, physical and biological pollutants modify the whole organism response, leading to nerve, cardiac, respiratory, reproductive, and skin system pathologies. Skin acts as a barrier for preventing pollutant modifications. This review aims to present the available scientific models, which help investigate the impact of pollution on the skin. The research question was “Which experimental models illustrate the impact of pollution on the skin in humans?” The review covered a period of 10 years following a PECO statement on in vitro, ex vivo, in vivo and in silico models. Of 582 retrieved articles, 118 articles were eligible. In oral and inhalation routes, dermal exposure had an important impact at both local and systemic levels. Healthy skin models included primary cells, cell lines, co-cultures, reconstructed human epidermis, and skin explants. In silico models estimated skin exposure and permeability. All pollutants affected the skin by altering elasticity, thickness, the structure of epidermal barrier strength, and dermal extracellular integrity. Some specific models concerned wound healing or the skin aging process. Underlying mechanisms were an exacerbated inflammatory skin reaction with the modulation of several cytokines and oxidative stress responses, ending with apoptosis. Pathological skin models revealed the consequences of environmental pollutants on psoriasis, atopic dermatitis, and tumour development. Finally, scientific models were used for evaluating the safety and efficacy of potential skin formulations in preventing the skin aging process or skin irritation after repeated contact. The review gives an overview of scientific skin models used to assess the effects of pollutants. Chemical and physical pollutants were mainly represented while biological contaminants were little studied. In future developments, cell hypoxia and microbiota models may be considered as more representative of clinical situations. Models considering humidity and temperature variations may reflect the impact of these changes.