Use of lipidomics to better understand skin properties

As a branch of metabolomics, lipidomics is aimed at full analysis of lipid species and their biological roles with respect to health and diseases. In the last ten years, it has attracted increasing attention as a research tool in a wide range of disciplines including physiology, lipid biochemistry, clinical biomarker discovery and pathology. Unless lipids were considered in the past to be only membrane components or an energy store, today we know they play critical roles in cell signaling transduction processes.[1,2] Furthermore, lipid metabolism is found to be critically aberrant in several different human diseases such as diabetes, obesity, atherosclerosis and Alzheimer’s disease[1-3]. Moreover, skin lipids are important for the formation of the outer layer of the epidermal barrier and contribute in various homeostatic processes including inflammatory and immune responses. All these characteristics make lipids profiling an essential tool not only for investigation of many pathological processes but also in identifying potential biomarkers for establishing preventive or therapeutic approaches for human health. Unlike other biomolecules, lipids do not possess a certain individual structure, making lipidomics analysis an analytical challenge in which mass spectrometry (MS) represents a powerful approach. Here we present a direct infusion MS approach (shotgun lipidomics) in order to detect and characterize several lipid species from human skin. First, the method was applied to several stratum corneum samples obtained from healthy volunteers in order to study the effects of bioactive compounds on lipid profile and the possible correlation with skin permeability. Second, the SSLs (skin surface lipids) was analyzed to measure squalene and its oxidation products. The different lipid species were identified (and semi-quantify) by means of the so called building block analysis (using LipidMaps as database). In other words, different fragmentation studies was performed in order to obtain all the structural information needed. Changing in skin lipid composition can represent a highly predictive biomarker of skin diseases as well as of aging.