Integrating multi-omics biomarkers and postprandial metabolism to develop personalized treatment for anorexia nervosa

Abstract

Background: Anorexia Nervosa (AN) is a serious mental illness characterized by emaciation, an intense fear of gaining weight despite being underweight, and distorted body image. Few treatments reverse the core symptoms in AN such as profound aversion to food and food avoidance. Consequently, AN has a chronic and relapsing course and the highest mortality rate of any psychiatric illness. A more complete understanding of the disease pathogenesis is needed in order to develop better treatments and improve AN outcome. The pathogenesis and psychopathophysiology of AN can be better elucidated by combining longitudinal phenotyping with multiple "omics" techniques, including genomics, proteomics, lipidomics, and metabolomics.

Design: This paper summarizes the key findings of a series of interrelated studies including new experimental data and previously published data, and describes our current initiatives and future directions.

Results: Exon sequencing data was analyzed in 1205 AN and 1948 controls. Targeted metabolomics, lipidomics, and proteomics data were collected in two independent convenience samples consisting of 75 subjects with eating disorders and 61 sex- and age-matched healthy controls. Study participants were female and the mean age was 22.9 (4.9 [SD]) years. Epoxide hydrolase 2 (EPHX2) genetic variations were significantly associated with AN risk, and epoxide hydrolase (sEH) activity was elevated in AN compared to controls. The polyunsaturated fatty acids (PUFAs) and eicosanoids data revealed that cytochrome P450 pathway was implicated in AN, and AN displayed a dysregulated postprandial metabolism of PUFAs and sEH-dependent eicosanoids.

Implication and current initiatives: Collectively, our data suggest that dietary factors may contribute to the burden of EPHX2-associated AN susceptibility and affect disease outcome. We are implementing new investigations using a longitudinal study design in order to validate and develop an EPHX2 multi-omics biomarker system. We will test whether sEH-associated postprandial metabolism increases AN risk and affects treatment outcome through an ω-6 rich breakfast challenge. Participants will include 100 ill AN patients, 100 recovered AN patients, and 100 age- and race-matched healthy women. These data will allow us to investigate 1) how genetic and dietary factors independently and synergistically contribute to AN risk and progression, and 2) if clinical severity and treatment response in AN are affected by sEH activity and eicosanoid dysregulation. Results of our study will 1) identify clinically relevant biomarkers, 2) unravel mechanistic functions of sEH, and 3) delineate contributory roles of dietary PUFAs and cytochrome P450 pathway eicosanoids for the purpose of developing novel AN treatments and improving disease prognosis.

Keywords: Anorexia nervosa; Bioactive lipid mediators; Cytochrome P450 pathway; EPHX2; Eating disorder; Epoxides and diols; Genetic polymorphism; Inflammation; Inflammatory biomarkers; Lipidomics; Metabolomics; Nutritional intervention; Personalized treatment development; Polyunsaturated fatty acids; Psychiatric metabolomics; Soluble epoxide hydrolase.

Figure 1

Health Implications of Soluble Epoxide Hydrolase’s Catalytic Actions

Figure 2

Overarching EPHX2 Omics Hypothesis in AN

Figure 3. Postprandial shift of diol-fatty acids (eicosanoids)

Differential postprandial metabolism observed between AN patients and healthy controls in ω-6 PUFA ARA diol-fatty acid (upper) but not in ω-3 PUFA DHA diol-fatty acid(lower).

Figure 4. Product-to-substrate ratios of eicosanoids (diol fatty acid:epoxy fatty acid)

Adapted from Shih et al, 2016 (Molecular Psychiatry). Result columns are of the form eicosanoid ratios based on absolute eicosanoid value in nanomole (nM). All individual eicosanoid were log-transformed (natural-log) before ratio-transformation and inferential statistical analysis. Statistical comparisons among three groups (Ill AN n=10, recovered AN n=10, controls n=38) were tested by age-adjusted ANOVA.