LIPIDOMICS

Lipidomics Data Analysis

Gain insights into the complex interactions between different lipid classes and their impact on health and disease.

Absolute Quantification
Reproducible Results
Comprehensive Lipid Class Coverage

View Brochure

Demo our Platform$

View Brochure

Demo our Platform

Speak to a Metabolomics Expert Today

Request a quote, get detailed information on sample types, or learn how metabolomics can accelerate your research.

First Name(Required)

Last Name(Required)

Email(Required)

Company Name(Required)

This field is hidden when viewing the form

Industry(Required)

Country(Required)

State(Required)

Territory(Required)

Marketing Opt-in

I would like to receive information from Metabolon

By submitting this form, you agree to our Terms of Use, Privacy Policy, and Cookie Policy.

This field is hidden when viewing the form

FormSubmittedURL

This field is hidden when viewing the form

UTM Medium

This field is hidden when viewing the form

UTM Source

This field is hidden when viewing the form

UTM Campaign

This field is hidden when viewing the form

UTM Content

This field is hidden when viewing the form

UTM Term

This field is hidden when viewing the form

GCLID

Reveal Lipid Insights

Understand the Role of Lipidomics Analysis

Lipidomics analysis is a branch of metabolomics focused on the study of lipids, the diverse group of molecules that play critical roles in cell structure, energy storage, and signaling. By analyzing the lipid profile of biological samples, lipidomics helps to uncover the complex interactions between different lipid species and their involvement in various physiological processes, including inflammation, cardiovascular disease, and neurological disorders. Lipids encompass a vast array of molecular species, including but not limited to phospholipids, sphingolipids, triglycerides, sterols, and fatty acids. Their structural diversity—ranging from varied headgroups to complex fatty acid compositions—creates a rich tapestry of biological functions, making lipidomics a critical yet intricate field of study.

Unravel Complex Data

Advancements in Lipidomics Analysis Services

Advances in lipidomics technologies have significantly enhanced our ability to analyze and understand lipid metabolism and its role in health and disease. Improved technologies, such as high-resolution mass spectrometry and advanced chromatography techniques, have enabled more precise identification and quantification of lipid species, allowing researchers to capture complex lipid profiles with greater accuracy. These advancements have led to deeper insights into lipid-related diseases, including cardiovascular disorders, neurodegenerative diseases, and metabolic conditions.

Our Lipidomics Solutions

Learn more about our lipidomics solutions to help you advance your research.

Complex Lipids Targeted Panel

Accurate quantitation of over 1000 lipid species across 14 classes.

View Product

Sphingolipids Targeted Panel

Measure changes in 61 lipid species across five lipid classes with strong links to inflammation.

View Product

Free Fatty Acids Targeted Panel

Study 7 free fatty acids associated with many disease states.

View Product

Fatty Acids Targeted Panel

Focus on 26 specific fatty acids and their metabolic pathways.

View Product

Oxysterols Targeted Panel

Measure 12 oxysterols and related sterols of biological significance.

View Product

Sebum Targeted Panel

Quantify 944 lipid species from sebum.

View Product

Stratum Corneum Targeted Panel

Screening for 350 lipid metabolites found in stratum corneum.

View Product

“Metabolon has developed a solid, scalable solution to the non-trivial problem of metabolomics biochemical interpretation, specifically tailored to their world-leading data acquisition platform. Leveraging decades of experience in data curation, Metabolon provides intuitive visualization tools for pathway analysis and disease association, adding even more value to an already outstanding product.”

David Broadhurst, PhD
Professor of BioSystems Data Science at Edith Cowan University, Australia.

Featured Resources

Learn more about our Complex Lipid Targeted Panel and how lipidomics can into your workflow. Find more resources here.

Complex Lipids Targeted Panel Whitepaper

Sphingolipids and Phospholipids Webinar

Circulating Lipids Case Study

On Demand: Association between Sphingolipids and Phospholipids with Blood Pressure and Hypertension Across Multiple Population-Based Cohorts Find out more →

Complex Lipids Targeted Panel Technical Whitepaper Find out more →

Case Study: Circulating Lipids as Biomarkers of Host Inflammatory Responses to Acute Critical Illness Find out more →

GET STARTED

Talk with an expert

Request a quote, get detailed information on sample types, or learn how metabolomics can accelerate your research. Find our contact details are here.

Find us on:

Talk with a Metabolomics expert

Name(Required)

Email(Required)

Company Name(Required)

This field is hidden when viewing the form

Industry(Required)

Country(Required)

State(Required)

Territory(Required)

ZIP/Postal Code(Required)

Enquiry Type(Required)

Message

Marketing Opt-in

I would like to receive information from Metabolon

By submitting this form, you agree to our Terms of Use, Privacy Policy, and Cookie Policy.

This field is hidden when viewing the form

FormSubmittedURL

This field is hidden when viewing the form

UTM Medium

This field is hidden when viewing the form

UTM Source

This field is hidden when viewing the form

UTM Campaign

This field is hidden when viewing the form

UTM Content

This field is hidden when viewing the form

UTM Term

This field is hidden when viewing the form

GLCID

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.