S89. INVESTIGATING METABOLIC DYSFUNCTION AND METABOLOMIC PROFILE CHANGES IN ANTIPSYCHOTIC NAIVE PATIENTS

BACKGROUND: Antipsychotics (APs) are the cornerstone of treatment for severe mental illnesses (SMI) but are associated with significant metabolic side-effects. Individuals who are young, and previously unexposed to AP treatment represent the group that is most vulnerable to AP-metabolic adverse effects. However, mechanisms underlying AP-induced weight gain and other abnormalities are poorly understood. Beyond AP-metabolic adverse effects, intrinsic metabolic dysregulation may characterize schizophrenia spectrum illnesses, although this has been difficult to disentangle from the multitude of lifestyle and medication factors that characterize disease course. Metabolomics (analysis of an organism’s metabolites) represents a novel method to examine biochemical pathways related to illness psychopathology and drug related metabolic adverse effects. METHODS: Anthropometric measures, fasting bloodwork, 2-hr oral glucose tolerance tests, clinical global impression scale scores, and targeted metabolomic analysis were completed for healthy controls (n=5) at baseline, and AP-naïve patients (n=25) at baseline and 3 months post initiation of APs. The first objective was to compare anthropometrics measures, fasting bloodwork, and metabolomic signatures between AP-naïve participants (at baseline) and healthy controls (matched for age and sex) to examine the effects of ‘illness’, pre-medication use. The second objective was to examine pre- and 3 month post-medication effects in AP-naïve patients for: i) anthropometric measures, fasting bloodwork, 2hr-oral glucose tolerance tests, and metabolomic signatures; and ii) compare metabolomic signatures across cohorts of AP-naïve participants who did, and who did not experience weight gain (i.e. a <2% or >5% body weight gain). RESULTS: Through independent and paired t-test analysis, metabolomic analysis showed significantly lower levels of serine (p=.0215), asparganine (p=0.0180), glycine (p=.0710), cysteine (p= .0177), and specific acylcarnitines (C20:1, C18:1, L-Car, C18:2, C20:2, C18:2-OH, C8:1, C:2, C20:0, C18, FDR=<.2, p<.05), but higher free fatty acids (20:4 (n-6), 22:0, 14:1 (n-5), 20:5 (n-3), 24:1, FDR=<.2, P<.05) in AP-naïve participants versus controls. From baseline to endpoint, paired sample t-tests for AP-naïve participants illustrated significant increases in weight (p=.000), waist circumference (p=.025), and body mass index (p=.000), and a significant decrease in clinical global impression scale scores (p=.002). Among AP-naïve participants who gained weight as compared to those who did not (n=3 for <2% and n=9 for >5% body weight increase)), aspartic acid and serine levels were higher (FDR=<.2 p<.05). DISCUSSION: Differences in metabolomic signatures are seen in patients before AP initiation (as compared to non-psychiatrically ill controls), possibly representing markers related to the endogenous risk of psychosis-spectrum illnesses. Additionally, specific amino acids may represent biomarkers predicting risk of antipsychotic induced weight gain after AP treatment initiation. Amino acids, free fatty acids, and acylcarnitines could be potential targets of the pathoetiology of psychosis-spectrum illnesses given their role in cell bioenergetics and neuronal dysfunction.