Evidence map›Paper›PMID 39948527›Full record

ArticleBMC psychiatry2025

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

Arish Mudra Rakshasa-Loots, Christina Steyn, Duncan Swiffen, Katie F M Marwick, Robert K Semple, Rebecca M Reynolds, Karl Burgess, Stephen M Lawrie, Stafford L Lightman, Saturnino Luz and 1 more

Abstract read
In one paragraph

Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Arish Mudra Rakshasa-LootsDivision of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Christina SteynDivision of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Duncan SwiffenDivision of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Katie F M MarwickDivision of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Robert K SempleCentre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
Rebecca M ReynoldsCentre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
Karl BurgessInstitute of Quantitative Biology, Biochemistry & Biotechnology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK.
Stephen M LawrieDivision of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Stafford L LightmanHenry Wellcome Laboratories for Integrative Neuroscience and Endocrinology, Translational Health Sciences, Faculty of Health Sciences, University of Bristol, Bristol, UK.
Saturnino LuzCentre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, UK.
Daniel J SmithDivision of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK. d.smith@ed.ac.uk.

Funding

Medical Research Council MR/Z503563/1
6 · The paper itself

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.

Indexed as

Bipolar DisorderMajor Depressive DisorderSchizophreniaAdolescentAdultBiomarkersFemaleHumansMaleMetabolomicsObservational Studies as TopicProspective StudiesScotlandYoung AdultBiomarkersBiomarkersBipolar disorderCircadian rhythmsDepressionMetabolomicsPsychosisSchizophreniaSleepSymptoms

Identifiers

PMID39948527
PMCPMC11827341

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.