Sebum Targeted Panel

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Sebum Targeted Panel

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About Sebum

Sebum is a complex mixture of lipids secreted by mature sebocytes onto the surface of the skin. Sebum may have antimicrobial, photoprotection, and vitamin delivery functions. Changes in the concentration and composition of sebum are related to acne and other skin disorders. Sebum is comprised of an unusual mix of lipid classes that is remarkably different in quantity and quality from lipids found in other organs. Major components are triglycerides, wax esters, squalene, and free fatty acids. The fatty acid composition of the complex lipids and the free fatty acid fraction is unique to human skin. Large amounts of the unusual sapienic acid (16:1n10), as well as a variety of odd and branched chain fatty acids, are present.

Metabolomics reveals biological insights otherwise unseen. For a successful metabolomics study, both small molecule discovery and the ability to dig deeper into specific biomarkers of interest are needed to uncover actionable insights that propel new therapeutic developments. A specific combination of gas or liquid chromatography-mass spectrometry (GC/MS or LC-MS) technology and biochemical expertise is required to identify these biomarkers of interest and develop assays that are sensitive enough to explore them fully.

At Metabolon, we understand the crucial role sebum plays in skin disorders, and we’ve established best-in-class expertise to identify and quantify its lipid components. This panel focuses on specific sebum lipids and their metabolic pathways and can be used to track biomarkers and enhance biological understanding across preclinical and clinical research.

Sebum Targeted Panel Details

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GC/MS-FAME Analysis
Lipid Class Measured Lipid Species
Total Fatty Acids 31
Saturated – Straight Chain 12:0, 13:0, 14:0, 15:0,
16:0, 17:0, 18:0, 20:0,
21:0, 22:0, 23:0, 24:0
Saturated – Branched Chain 12:0-iso, 13:0-iso,
13:0-anteiso, 14:0-iso,
15:0-iso, 15:0-anteiso,
16:0-iso, 17:0-anteiso,
18:0-iso, 19:0-anteiso,
20:0-iso, 21:0-iso,
21:0-anteiso
Unsaturated – Straight Chain 16:1n10, 18:2n10, 16:1n7,
18:2n6, 18:3n3, 18:1n10/18:1n9
FIA-MRM-MS Analysis
Lipid Class Abbreviation Number of Species
Cholesterol Esters CE 26
Diacylglycerols DAG 47
Squalene SQ 1
Triacylglycerols TAG 575
Wax Esters WE 295
Total 944
Disclaimer: This method is for Research Use Only and is not to be used for diagnostic purposes.

Delivering Absolute Quantification for Research and Biomarker Analysis

Our readily available or custom developed quantitative assays help you achieve your research and biomarker validation objectives with precise and fully validated methods. Our targeted assays and panels cover >1,000 metabolites and lipids across a wide range of biochemical classes, metabolic pathways, and physiological processes, and they can be customized to best fit any application.

Sebum Targeted Panel Applications

Personal Care & Cosmetics

Metabolon’s technology can provide a comprehensive survey of the skin metabolome and microbiome from a range of non-invasive skin sampling options, including our proprietary sample preparation process that allows subjects to provide samples using commercially available tape strips. In addition to the Metabolon Global Discovery Panel, we can quantitatively measure hundreds of lipid analytes on our pre-existing skin lipid panels. With the ability to capture biomarkers of wound repair, UV exposure, hydration, environmental exposures, and more, our proprietary platform has helped researchers understand skin conditions as diverse as dandruff, atopic dermatitis, psoriasis, acne, and aging.
Personal Care & Cosmetics

Big Insights with Metabolon

Cited in over 3,000 publications, we help scientists and manufacturers gain greater insight into their studies through metabolomics. See how our approach can become a successful part of your workflow.

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References

1. Zgoda-Pols, J.R., et al., Metabolomics analysis reveals elevation of 3-indoxyl sulfate in plasma and brain during chemically-induced acute kidney injury in mice: investigation of nicotinic acid receptor agonists. Toxicol Appl Pharmacol, 2011. 255(1): p. 48-56.

2. Bryant, J.A., et al., The impact of an oral purified microbiome therapeutic on the gastrointestinal microbiome. Nat Med, 2026. 32(1): p. 186-196

3. McGovern, B .H., et al., SER-109, an Investigational Microbiome Drugto Reduce Recurrence After Clostridioides difficile Infection: Lessons Learned From a Phase 2 Trial. Clin Infect Dis, 2021. 72(12): p. 2132-2140.

4. Feuerstadt, P., et al., SER-109, an Oral Microbiome Therapy for Recurrent Clostridioides difficile Infection. N Engl J Med, 2022. 386(3): p. 220-229.

5. Hu, Z., et al., Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer. Mol Oncol, 2025. 19(6): p. 1737-1750.

6. Butler, F.M., et al., Vegetarian Dietary Patterns and Diet-Related Metabolites Are Associated With Kidney Function in the Adventist Health Study-2 Cohort. J Ren Nutr, 2025.

7. Stanford, J., et al., Metabolomic Profiling and Diet Quality Scoring in a Randomized Crossover Trial of Healthy and Typical Dietary Patterns. Mol Nutr Food Res, 2025 . 69(23): p. e70271.

8. O’Connor, L.E., et al., Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial. J Nutr, 2023. 153(8): p. 2181-2192.

9. Fritsch, D.A., et al., Microbiome function underpins the efficacy of a fiber-supplemented dietary intervention in dogs with chronic large bowel diarrhea. BMC Vet Res, 2022. 18(1): p. 245.

10. Leal, L.N., et al., Preweaning nutrient supply improves lactation productivity and reduces the risk of culling in Holstein cows. J Dairy Sci, 2025. 108(6): p. 5875-5888.

11. Ahsin, M., et al., Soil and pasture health underlie improved beef nutrient density determined by untargeted metabolomics in Southern US grass finished beef systems. NPJ Sci Food, 2025. 9(1): p. 151.

12. Yin, W., et al., Plasma lipid profiling across species for the identification of optimal animal models of human dyslipidemia. J Lipid Res, 2012. 53(1): p. 51-65.

13. Porter, F .D., et al., Cholesterol oxidation products are sensitive and specific blood-based biomarkers for Niemann-Pick C1 disease. Sci Transl Med, 2010. 2(56): p. 56ra81.

14. Needham, B .D., et al., Plasma and Fecal Metabolite Profiles in Autism Spectrum Disorder. Biol Psychiatry, 2021. 89(5): p. 451-462

15. Li, C., et al., Estradiol and mTORC2 cooperate to enhance prostaglandin biosynthesis and tumorigenesis in TSC2-deficient LAM cells. J Exp Med, 2014. 211(1): p. 15-28.

16. Green, P.G., et al., Metabolic flexibility and reverse remodelling of the failing human heart. Eur Heart J, 2025. 46(25): p. 2422-2433.

17. Maekawa, H., et al., SGLT2 inhibition protects kidney function by SAM-dependent epigenetic repression of inflammatory genes under metabolic stress. J Clin Invest, 2025. 135(19).

18. Wu, D., et al., Integrated screens reveal that guanine nucleotide depletion, which is irreversible via targeting IMPDH2, inhibits pancreatic cancer and potentiates KRAS inhibition. Gut, 2026.

19. Schwerdtfeger, L.A., et al., Gut microbiota and metabolites are linked to disease progression in multiple sclerosis. Cell Rep Med, 2025. 6(4): p. 102055.

20. Wu, H., et al., Microbiome-metabolome dynamics associated with impaired glucose control and responses to lifestyle changes. Nat Med, 2025. 31(7): p. 2222-2231.

21. Jacobs, J.P., et al., Cognitive behavioral therapy for irritable bowel syndrome induces bidirectional alterations in the brain-gut-microbiome axis associated with gastrointestinal symptom improvement. Microbiome, 2021. 9(1): p. 236.

22. Pietzner, M., et al., Plasma metabolites to profile pathways in noncommunicable disease multimorbidity. Nat Med, 2021. 27(3): p. 471-479.

23. Faquih, T.O., et al., Robust Metabolomic Age Prediction Based on a Wide Selection of Metabolites. J Gerontol A Biol Sci Med Sci, 2025. 80(3).

24. Scherer, N., et al., Coupling metabolomics and exome sequencing reveals graded effects of rare damaging heterozygous variants on gene function and human traits. Nat Genet, 2025. 57(1): p. 193-205.

25. Holmes, Z.C., et al., Untargeted metabolomic analysis of human milk from healthy mothers reveals drivers of metabolite variability. Sci Rep, 2024. 14(1): p. 20827.

26. Titz, B., et al., Implications of Ocular Confounding Factors for Aqueous Humor Proteomic and Metabolomic Analyses in Retinal Diseases. Transl Vis Sci Technol, 2024. 13(6): p. 17.

27. Bloom, S.M., et al., Cysteine dependence of Lactobacillus iners is a potential therapeutic target for vaginal microbiota modulation. Nat Microbiol, 2022. 7(3): p. 434-450.

28. Leimer, E.M., et al., Lipid profile of human synovial fluid following intra-articular ankle fracture. J Orthop Res, 2017. 35(3): p. 657-666.