The associations between metabolic profiles and sexual and physical abuse in depressed adolescent psychiatric outpatients: an exploratory pilot study

Abstract

Background : Sexual and physical abuse have been associated with long-term systemic alterations such as low-grade inflammation and changes in brain morphology that may be reflected in the metabolome. However, data on the metabolic consequences of sexual and physical abuse remain scarce. Objective : This pilot study sought to investigate changes in the metabolite profile related to sexual and physical abuse in depressed adolescent psychiatric outpatients. Method : The study included 76 patients aged 14–18 years, whose serum samples were analysed with a targeted metabolite profiling methodology. We estimated the associations between metabolite concentrations and the Trauma and Distress Scale (TADS) Sexual and Physical Abuse factor scores using three linear regression models (one unadjusted and two adjusted) per metabolite and trauma type pair. Additional variables in the two adjusted models were 1) the lifestyle indicators body mass index, tobacco use, and alcohol use, and 2) depression scores and the chronicity of depression. Results : TADS Sexual Abuse scores associated positively with homogentisic acid, as well as cystathionine, and negatively with choline in linear regression analysis, whereas TADS Physical Abuse scores associated negatively with AMP, choline, γ-glutamyl cysteine and succinate, and positively with D-glucuronic acid. Conclusions : This pilot study did not include a healthy control group for comparison and the cohort was relatively small. Nevertheless, we observed alterations in metabolites related to one-carbon metabolism, mitochondrial dysfunction, oxidative stress, and inflammation in depressed patients with a history of sexual or physical abuse.

An exploratory study of metabolomics in endogenous and cannabis-use-associated psychotic-like experiences in adolescence

“…Background variables with possible effects on metabolism were used as covariates in the regression models, which were based on previous ndings indicating relevance, as described in our previous article (Kurkinen et al, 2021). These included gender, age, BMI, IDQ, ongoing medications, depression chronicity, BDI, TADS (Kurkinen et al, 2023), ISI, PSQI, tobacco smoking, cannabis use (Hinckley et al, 2022), and alcohol use (ASSIST and AUDIT-C). In addition to the unadjusted Model 1, ve adjusted linear models were estimated with the covariates correlating with the six symptom dimensions (Supplementary Table 3).…”