Julian Mutz, Lachlan Gilchrist, Andrea G Allegrini, Sandra Sanchez Roige, Cathryn M Lewis
{"title":"Metabolomic ageing across mental and behavioural disorders.","authors":"Julian Mutz, Lachlan Gilchrist, Andrea G Allegrini, Sandra Sanchez Roige, Cathryn M Lewis","doi":"10.1136/bmjment-2025-302181","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Individuals 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.</p><p><strong>Objective: </strong>To examine whether metabolomic ageing differs across mental disorders and whether associations vary by sex, age group and genetic liability.</p><p><strong>Methods: </strong>Using 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.</p><p><strong>Findings: </strong>Among 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.</p><p><strong>Conclusions: </strong>Metabolomic 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.</p><p><strong>Clinical implications: </strong>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.</p>","PeriodicalId":72434,"journal":{"name":"BMJ mental health","volume":"29 1","pages":""},"PeriodicalIF":6.6000,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13288872/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ mental health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/bmjment-2025-302181","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Individuals 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.
Objective: To examine whether metabolomic ageing differs across mental disorders and whether associations vary by sex, age group and genetic liability.
Methods: Using 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.
Findings: Among 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.
Conclusions: Metabolomic 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.