Abstract
Facial skin redness can be an indicator of skin inflammation, however the physiological connection between facial redness and inflammatory status, as well as its role in age-related skin changes, remains poorly understood. This study aims to investigate the association between the pattern of facial skin redness and biological inflammatory status, as well as age-related changes occurring in the skin. Four studies were conducted recruiting healthy Northern Asian females. Disordered spatial patterns of facial skin redness signals were assessed using image analysis, i.e., the a* gradient algorithm, which quantifies the disordered shape and pattern of localized redness signals on facial skin. This redness pattern was compared with (1) inflammatory protein markers (IL-1Ra/ IL-1α and IL-8) measured from stripped corneocyte samples, (2) gene expression profiles obtained through transcriptome analysis using skin biopsy samples, and (3) the distribution pattern of blood vessel measured using a photoacoustic microscope. The association between the skin redness pattern and current and future ageing-related skin changes was examined through a longitudinal study tracking the same subjects for 10 years. A significant correlation was observed between the a* gradient and the levels of inflammatory cytokines (IL-1Ra/IL-1α and IL-8). Transcriptome analysis revealed upregulation of genes related to acute inflammation, chronic inflammation, cellular senescence, and angiogenesis in subjects with higher a* gradients. The high a* gradient group exhibited an extension of blood vessel diameter and increased blood vessel density, while the medium a* gradient group only exhibited blood vessel extension. Lastly, the 10-year longitudinal study demonstrated that the a* gradient was associated with current and future skin ageing-related attributes, such as increased skin texture and wrinkle formation. The spatial pattern of localized redness on the skin reflects the biological inflammatory status, and this inflammatory condition helps predict current and future age-related skin changes.