Evidence map›Paper›PMID 42331621›Full record

ArticleBMJ mental health2026

Metabolomic ageing across mental and behavioural disorders.

Julian Mutz, Lachlan Gilchrist, Andrea G Allegrini, Sandra Sanchez Roige, Cathryn M Lewis

Abstract read
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Article in BMJ mental health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Julian MutzSocial, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England, UK julian.mutz@gmail.com.ORCID 0000-0001-5308-1957
Lachlan GilchristSocial, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England, UK.
Andrea G AllegriniSocial, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England, UK.
Sandra Sanchez RoigeDepartment of Psychiatry/Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA.
Cathryn M LewisSocial, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England, UK.

Funding

Wellcome Trust 226770/Z/22/Z
6 · The paper itself

Abstract

backgroundIndividuals with mental disorders face excess morbidity and premature mortality. Accelerated ageing has been proposed as a contributing mechanism but population-scale evidence across diverse diagnoses is limited.

objectiveTo examine whether metabolomic ageing differs across mental disorders and whether associations vary by sex, age group and genetic liability.

methodsUsing plasma metabolomic profiles from UK Biobank participants, we applied a metabolomic ageing clock (MileAge) to estimate disorder-specific differences between metabolite-predicted and chronological age. Mental disorders were ascertained from health records and self-reported physician diagnoses. We analysed nine diagnostic groups and 45 individual disorders and assessed sex and age group differences and associations with polygenic scores.

findingsAmong 225 212 participants (54% female; mean age 56.97), 38 524 had a diagnosis preceding baseline. Substance use, psychotic, affective and neurotic disorders were associated with a metabolite-predicted age older than chronological age, largest for psychosis (β=0.556, 95% CI 0.250 to 0.861, p<0.001). Obsessive-compulsive and eating disorders were associated with a metabolite-predicted age younger than chronological age. Several associations were stronger in males and in individuals aged <65 years. Higher genetic liability to depression, autism and attention-deficit/hyperactivity disorder predicted an older metabolomic age (β range=0.020 to 0.047), whereas polygenic scores for psychosis and tobacco use disorder predicted a younger metabolomic age (β range=-0.023 to -0.040). For obsessive-compulsive disorder and anorexia nervosa, clinical and genetic associations indicated younger metabolomic ageing.

conclusionsMetabolomic ageing in mental disorders is heterogeneous. While many disorders are associated with an older biological age, some are linked to a younger biological age. Divergence between genetic liability and clinical phenotypes suggests that non-genetic factors shape biological ageing differences. CLINICAL IMPLICATIONS: Biological age should not be assumed to uniformly exceed chronological age across mental disorders. Sex and age-specific approaches could improve understanding of biological ageing processes in psychiatry.

Indexed as

AgingMental DisordersMetabolomicsAdultAgedAge FactorsFemaleGenetic Predisposition to DiseaseGenetic Risk ScoreHumansMaleMiddle AgedSex FactorsUK BiobankUnited KingdomGenetics, BehavioralMental HealthPsychiatryPsychopathology

Identifiers

PMID42331621
PMCPMC13288872

What Socratic holds

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LicenceCC BY
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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 Socratic graph.