Paired proteomic analysis reveals protein alterations in sun-exposed skin of professional drivers - Amanda C. Camillo-Andrade; Lucas A. Sales; Juliana S. G. Fischer; Rosario Duran; Marlon D. M. Santos; Paulo C. Carvalho (Scientific Reports)
Abstract Professional drivers represent an ideal cohort for investigating the effects of solar radiation on skin due to their unique, asymmetric exposure to sun, a consequence of vehicle window orientations. Consequently, one side of the face is naturally subjected to more solar radiation, resulting in uneven sunlight exposure. This scenario supports a paired experimental design for precise within-individual comparisons, crucial for assessing sun exposure’s impact on skin health, including signs of aging. Leveraging this approach, our study reveals sun-induced overexpression of proteins linked to photoaging through paired proteomic analysis, providing novel insights into the skin’s adaptive responses to chronic solar exposure. Initially, our research focused on a dataset from ten male professional drivers, identifying a set upregulated proteins in sun-exposed skin compared to the less exposed side of the face. To validate these findings, we extended our investigation to a new cohort of seven female bus drivers. Our motivation in switching genders and utilizing different mass spectrometry equipment and sample preparation techniques was for assessing the robustness of our initial findings, encompassing not just sex differences but also methodological variations, and also for understanding the broader implications of our results for photodermatology. To enable this detailed analysis, we developed specialized software that allows precise paired proteomic analysis, significantly enhancing the robustness and clarity of our findings. Our results shortlisted keratins, S100A14, and F-box proteins—by remaining consistently overexpressed in sun-exposed skin—and hemoglobin subunit beta as downregulated across both cohorts. Our findings underscore the potential of proteomic techniques in advancing our understanding of the molecular dynamics of photoaging and highlight the value of selecting cohorts with specific exposure characteristics.