Establishing Endocannabinoid Levels in Metabolically Healthy Adults
Reliable diagnostic interpretation depends on the availability of well-characterized physiological reference ranges. For the endocannabinoid system, such reference intervals have not been established in a form suitable for clinical or translational application. This program is designed to generate those reference values through quantitative measurement and population-level analysis.
Why This Study Matters
The endocannabinoid system regulates mood, pain, metabolism, and immune function — yet no clinical reference range exists to assess whether it is functioning properly. This study is the first step toward changing that. By establishing baseline ECS levels in healthy adults, AMCANN is building the foundation for a standardized diagnostic test that could transform how physicians understand and treat a wide range of conditions.
Absence of Clinically Interpretable Reference Ranges in Endocannabinoid Biology
Standardized reference ranges underpin the clinical utility of most measurable biological systems, including lipid panels, endocrine markers, and metabolic indices. Comparable reference intervals for endocannabinoid concentrations have not been defined, not because of a lack of physiological relevance, but because of historical limitations in analytical capability.
Endocannabinoid signaling participates in multiple regulatory domains, including immune modulation, metabolic processes, and neurophysiological adaptation. However, the absence of reproducible quantitative measurements has limited its integration into diagnostic frameworks. Detection of endogenous cannabinoid ligands in human plasma requires high-sensitivity analytical methodologies capable of resolving low-abundance lipid signaling molecules within complex biological matrices.
Advances in liquid chromatography–tandem mass spectrometry (LC–MS/MS) have enabled reliable quantification of these compounds at physiologically relevant concentrations. This The program leverages these analytical capabilities to generate statistically robust distributions of endocannabinoid concentrations within metabolically defined populations, laying the foundation for subsequent biomarker interpretation and diagnostic applications.