The skin barrier function is affected by the lipid organisation of the stratum corneum (SC). Specifically, the ratios and chain-length distributions of ceramide subclasses within the extracellular lipid lamellae are important for skin barrier function. Two recent studies applying quantitative, high-resolution lipidomics to SC samples illustrate how subclass- and species-level resolution, rather than total lipid content, explain barrier outcomes in eczema and atopic dermatitis (AD).
Formulation benchmarking in eczema-prone skin
In a double-blind, split-body trial, 58 adults with a history of eczema received a multivesicular emulsion containing physiological lipids and glycerine (MVE+GL) on one arm and a standard oil-in-water emulsion with glycerine but no added lipids (OW+G) on the contralateral side, twice daily for 28 days. SC samples were collected by tape stripping at baseline and end-of-treatment, and profiled by mass spectrometry-based lipidomics, detecting, identifying, and quantifying over 1,600 lipid species, of which 364 were detected in more than 70% of samples from at least one treatment arm.
Both formulations increased raw lipid abundance to a similar degree (around 80 in each, with over 50 overlapping), but only MVE+GL produced twofold or more changes. Transepidermal water loss decreased significantly after MVE+GL treatment, whereas OW+G showed no change, indicating that MVE+GL improves skin barrier function. MVE+GL-treated sites also showed a reduced irritant response compared with OW+G.
At the subclass level, MVE+GL selectively increased ceramide subclasses with 18-carbon sphingoid bases (six of eight subclasses gained significance), including NP(18), AP(18), and AS(18), all consistently higher than in OW+G-treated skin. Species-level analysis identified ten lipids most strongly (negatively) correlated with TEWL20; MVE+GL increased six protective species from the AdS, NH, NP, and AS subclasses, while NdS species (associated with weaker barrier integrity) decreased upon treatment.
Microbiome–lipidome crosstalk in atopic dermatitis
Another study combined shotgun lipidomics with 16S microbial sequencing on tape-strip samples from lesional and non-lesional skin of 16 AD patients and 16 matched healthy controls. Lesional skin showed cholesterol-dominant lipid profiles, higher total lipid content, and reduced lipid diversity relative to non-lesional and healthy skin. Ceramide subclasses NS, NdS, NH, and AS were most abundant in lesional skin, decreasing along the lesional to non-lesional to healthy gradient, while EOH, EOS, AdS, AH, and AP subclasses showed the inverse pattern, reaching their lowest levels in lesional tissue.
Microbiome profiling showed elevated Staphylococcus abundance in both lesional and non-lesional AD skin relative to controls, with S. aureus enriched in lesions alongside reductions in S. melonis, Arthrobacter russicus, and S. aquatilis. Notably, S. hominis and Finegoldia magna were more abundant in non-lesional than in healthy skin. Correlation network analysis, built around Staphylococcus taxa given their outsized contribution to group differences, showed dense, interconnected lipid–microbe networks in non-lesional and healthy skin versus sparse, isolated modules in lesional skin.
Using reconstructed human epidermis (RHE) models mimicking AD, validated against lesional patient samples by lipid class and ceramide subclass overlap, the authors showed that S. hominis supplementation reduced the lesional-enriched species NdS 18:0;2/24:0;0, improved tissue architecture, and partially normalized AD-associated inflammatory signatures. Direct contact assays confirmed a reduction of this ceramide species by S. hominis, and in vivo, S. hominis abundance correlated with lower TEWL, while NdS 18:0;2/24:0;0 correlated with impaired barrier function.
Implications for skin barrier R&D
Both studies point to the same methodological conclusion: subclass- and species-resolved ceramide profiling, not a total lipid overview, distinguishes effective interventions from ineffective ones. This tool also reveals molecular mechanisms that bulk lipidome measurements miss. In formulation testing, detailed lipidomics analysis explains why products with a similar total increase in stratum corneum lipid content produce different barrier outcomes – a distinction that bulk lipid measurement alone cannot account for. In disease biology, lipidomics analysis allows the study of the specific microbe–lipid interaction underlying the S. hominis effect described above. For skin barrier R&D, this level of detail is becoming the baseline expectation — for benchmarking emollients, characterizing disease-associated lipid signatures, and evaluating microbiome-based interventions.
Relevant skin lipidomics case studies: https://www.lipotype.com/lipidomics-applications/tags-dermatology/
Contact
Olya Vvedenskaya, MD, PhD
