Abstract Dr. Shih is a long-term collaborator of ours and her work on patients with anorexia nervosa is a direct extension of the parent grant (“Bioactive lipids as effectors and indicators of the deleterious effects of environmental exposure on chronic diseases”). Dr. Shih’s proposed research directly relates and complements to Goal 5 of the parent grant (Test the hypothesis that toxicity and disease states can be altered by pharmacological intervention with and without nutritional intervention) and supports the NIEHS mission to understand the regulatory functions of chemicals and the xenobiotic exposure on human health. Dr. Shih’s recent human subjects and epidemiological studies revealed several new findings relating to how sEH and PUFA-derived bioactive lipids (oxylipins) are dysregulated in anorexia nervosa (AN) subjects. The most intriguing finding was the opposite directional association with symptom severity when comparing n- 3-derived versus n-6-derived diols oxylipins. This finding reveals the need to clarify the role of oxylipins in human health and how dietary nutrition affects them. Here-in, we are proposing to “marry” the expertise of an epidemiologist (Dr. Shih) to the data and knowledge accumulated over the last 25 years in the Hammock laboratory to investigate the role of bioactive lipids in heath and diseases through numerous animal studies and human subject data. Dr. Shih will conduct a focused, multi-species analytical approach to meta-analyze data from the decades’ worth of research work in the Hammock’s lab to effectively explore each oxylipin’s role in the context of disordered health. The meta- analysis approach will remove the issue of limited power within individual studies, increase generalizability of disorder-heath association, lessen assay-associated confounds, and generate new hypotheses. The completion of this research will yield high-confidence conclusions for the role of oxylipins in human health and disorders. The unifying analytical methods and comparative study design will lead to discovery of functional implications of metabolomic data that is critical for establishing clinical biomarkers of high validity and reproducibility.