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Metabolic biomarkers of clinical outcomes in severe mental illness (METPSY): protocol for a prospective observational study in the Hub for metabolic psychiatry

2025/02/13 by Arish Mudra Rakshasa-Loots, Christina Steyn, Duncan Swiffen +8 · 1 voice
Biochemistry, Genetics and Molecular Biology · Medicine · Neuroscience · #Diet and metabolism studies #Metabolomics and Mass Spectrometry Studies #Tryptophan and brain disorders

paper · pdf · doi:10.1186/s12888-025-06579-9

openalex publication_date 2025/02/13 · openalex created_date 2025/02/14 · openalex updated_date 2026/08/03

Abstract

People with severe mental illness have high rates of obesity, type 2 diabetes, and cardiovascular disease. Emerging evidence suggests that metabolic dysfunction may be causally linked to the risk of severe mental illness. However, more research is needed to identify reliable metabolic markers which may have an impact on mental health outcomes, and to determine the mechanisms behind their impact. In the METPSY research study, we will investigate the relationship between metabolic markers and clinical outcomes of severe mental illness in young adults. We will recruit 120 young adults aged 16-25 years living in Scotland with major depressive disorder, bipolar disorder, schizophrenia, or no severe mental illness (controls) for a prospective observational study. We will assess clinical symptoms at three in-person visits (baseline, 6 months, and 12 months) using the Structured Clinical Interview for DSM-5, and collect blood samples at each of these visits for agnostic profiling of metabolic biomarkers through an untargeted metabolomic screen, using the rapid hydrophilic interaction liquid chromatography ion mobility mass spectrometry method (RHIMMS). Participants will also complete remote assessments at 3 and 9 months after the baseline visit: Ecological Momentary Assessments to measure mental health, wrist actigraphy to measure rhythms of rest and activity, and continuous glucose monitoring to measure metabolic changes. Throughout the 12-month enrolment period, we will also measure objective markers of sleep using a radar sleep monitor (Somnofy). Using advanced statistical techniques and machine learning analysis, we will seek to better understand the mechanisms linking metabolic health with mental health in young adults with schizophrenia, bipolar disorder, and severe depression. Clinical trial number: Not applicable.

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