Skin
volatile emissions offer a noninvasive insight into
metabolic
activity within the body as well as the skin microbiome and specific
volatile compounds have been shown to correlate with age, albeit only
in a few small studies. Building on this, here skin volatiles were
collected and analyzed in a healthy participant study (n = 60) using a robust headspace-solid phase microextraction (HS-SPME)
gas chromatography–mass spectrometry (GC-MS) workflow. Following
processing, 18 identified compounds were deemed suitable for this
study. These were classified according to gender influences and their
correlations with age were investigated. Finally, 6 volatiles (of
both endogenous and exogenous origin) were identified as significantly
changing in abundance with participant age (p < 0.1). The potential origins of these dysregulations are discussed.
Multiple linear regression (MLR) analysis was employed to model age
based on these significant volatiles as independent variables, along
with gender. Our analysis shows that skin volatiles show a strong
predictive ability for age (explained variance of 68%), stronger than
other biochemical measures collected in this study (skin surface pH,
water content) which are understood to vary with chronological age.
Overall, this work provides new insights into the impact of aging
on the skin volatile profiles which comprises both endogenously and
exogenously derived volatile compounds. It goes toward demonstrating
the biological significance of skin volatiles and will help pave the
way for more rigorous consideration of the healthy “baseline”
skin volatile profile in volatilomics-based health diagnostics development
going forward.