Fatty acids play many physiologically important roles in an organism. They are not only key metabolites of energy storage and production but also the basic building blocks of complex lipids that form cellular membranes. A variety of bioactive forms of fatty acid metabolites, known as lipid mediators, act as local hormones and are involved in many physiological systems and pathological processes (eg, eicosanoids, lysophospholipids, resolvins, protectins, maresins). Dysregulation of fatty acid metabolism has been associated with many diseases.
Metabolomics reveals biological insights otherwise unseen. In a successful metabolomics study, both small molecule discovery and the ability to dig deeper into specific biomarkers of interest can uncover actionable insights that propel new therapeutic developments. Liquid chromatography-mass spectrometry (LC-MS) technology and expertise are 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 that fatty acids play in disease, and we’ve established best-in-class expertise. This panel focuses on specific fatty acids and their metabolic pathways and can be used to track biomarkers and enhance biological understanding across preclinical and clinical research.
(Scroll left/right to see full table)
| LLOQa | |
|---|---|
| Metabolite | Plasma/Serum |
| Myristic Acid (14:0) | 1.00 µg/mL |
| Pentadecanoic Acid (15:0) | 0.600 µg/mL |
| Palmitic Acid (16:0) | 8.00 µg/mL |
| Stearic Acid (18:0) | 4.0 µg/mL |
| Arachidic Acid (20:0) | 1.00 µg/mL |
| Myristoleic Acid (14:1n5) | 0.600 µg/mL |
| Palmitoleic Acid (16:1n7) | 1.00 µg/mL |
| Vaccenic Acid (18:1n7) | 1.00 µg/mL |
| Oleic Acid (18:1n9) | 8.00 µg/mL |
| Cis-11-Eicosaenoic Acid (20:1n9) | 0.600 µg/mL |
| Mead Acid (20:3n9) | 1.00 µg/mL |
| Linoleic Acid (18:2n6) | 8.00 µg/mL |
| Gamma-Linolenic Acid (18:3n6) | 0.600 µg/mL |
| Dihomo-Gamma-Linolenic Acid (20:3n6) | 1.00 µg/mL |
| Arachidonic Acid (20:4n6) | 6.00 µg/mL |
| Adrenic Acid (22:4n6) | 0.600 µg/mL |
| Osbond Acid (22:5n6) | 0.600 µg/mL |
| Cis-11,14-Eicosadienoic Acid (20:2n6) | 1.00 µg/mL |
| Alpha-Linolenic Acid (18:3n3) | 0.600 µg/mL |
| Stearidonic Acid (18:4n3) | 0.600 µg/mL |
| Eicosatetraenoic Acid (ETA) (20:4n3) | 0.600 µg/mL |
| Eicosapentaenoic Acid (EPA) (20:5n3) | 1.00 µg/mL |
| Docosapentaenoic Acid (22:5n3) | 1.00 µg/mL |
| Docosahexaenoic Acid (DHA) (22:6n3) | 2.00 µg/mL |
| Margaric Acid (17:0) | 1.00 µg/mL |
| Cis-13-16-Docosadienoic Acid (22:2n6) | 0.600 µg/mL |
aLower Limit of Quantitation (LLOQ) varies for each sample type.
Fatty acids are determined by GC-MS (Agilent 7890A/5975C) as their respective methyl esters after conversion of all free and conjugated fatty acids into methyl esters (FAME Analysis). The Fatty Acids Metabolism Targeted Panel measures the total fatty acid content of 28 fatty acids in a variety of matrices.
(Scroll left/right to see full table)
| Sample Type | Sample Requirements |
|---|---|
| Plasma/Serum | ≥ 150 µL |
Others on request
Disclaimer: This panel is for Research Use Only and is not to be used for diagnostic purposes.
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 more than 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.
Dysregulated metabolism is essential for the growth and proliferation of individual cancer cells, but the physiology of the patient is as much a part of the equation as the tumor. Metabolomics can both identify cancer-specific drug targets and assess the patient’s phenotype more broadly, addressing key questions such as: Who will respond to the therapy? How can we expand the pool of responders? How can we predict adverse events? Overall, metabolomics informs decision-making and positions development programs for success by providing a functional readout of the molecular phenotype.
Diabetes is a serious metabolic condition affecting more than 37 million Americans and 460 million people worldwide according to the most recent report from the Centers for Disease Control. Despite being a worldwide epidemic, much remains unknown about individual risk factors for diabetes development, and research is currently being done to identify new and effective treatment for diabetes at all stages. By facilitating assessment of specific metabolic pathways impacted by diabetes, targeted metabolomics can be a critical tool used to identify biomarkers of disease development for early intervention and novel targets to control disease progression, as well for the development of new pharmaceuticals with specific mechanisms of action.
It is well-established that a low-carbohydrate, high-fat ketogenic diet (KD) can help treat refractory epilepsy, which affects more than a third of epileptic patients who don’t respond to existing anticonvulsive drugs. What scientists haven’t understood until recently is how this kind of diet translates to brain activity. The answer for this aspect of epilepsy lies in the gut microbiome. There are many other neurological disorders like Alzheimer’s disease, ALS, Parkinson’s disease, and more. While so much remains to be understood about brain science, we do know that metabolomics is uniquely poised to understand the brain because of the ability of metabolites, small molecules, to cross the blood-brain barrier providing unique insights.
Metabolomics can be essential for investigating the association between nutrition and health status, as metabolites represent a functional readout at the interface between diet and the complex metabolic systems that influence both health and disease. By illuminating the interactions of metabolites throughout the body within defined pathways, targeted metabolomics can help investigators gain new insights into the absorption and digestion of diet-derived macronutrients, monitor metabolism by various organ systems, and subsequently assess the underlying biology of various health and disease states.
Heart failure is a leading cause of death worldwide, and there are numerous factors that lead to this and other cardiovascular diseases (CVD). Metabolomics can illuminate cardiovascular disease at multiple levels. In preclinical studies, such as with cardiomyocytes or heart tissue from model organisms, understanding mitochondrial function, energetics, and redox status can drive critical insights into disease mechanism. In human studies, metabolomics offers the opportunity to account for well-established CVD risk factors such as cholesterol and complex lipids, while simultaneously profiling thousands of other biochemicals in an unbiased fashion to enable the discovery of novel disease mechanisms and biomarkers.
Once you see the full value of metabolomics, the only remaining question is: who does it best? While many laboratories have metabolite profiling or analytical chemistry capabilities, comprehensive metabolomics technologies are extremely rare.
Accurate, unbiased metabolite identification across the entire metabolome introduces signal-to-noise challenges that very few labs are equipped to handle. Also, translating massive quantities of data into actionable information is slow, if not impossible, for most because proper interpretation takes two things that are in short supply: experience and a comprehensive database.
Using our robust platform and visualization tools, our experts are uniquely able to tell you more about your molecule and develop assay panels to help you zero in on the results you need.
Coverage
Ability to interrogate thousands of metabolites across diverse biochemical space, revealing new insights and opportunities
Comparability
Ability to integrate the data from different studies into the same dataset, in different geographies, among different patients over time
Competency
Ability to inform on proper study design, generate high‐quality data, derive biological insights, and make actionable recommendations
Capacity
Ability to process hundreds of thousands of samples quickly and cost‐efficiently to service rapidly growing demand
