The BMIgap tool to quantify transdiagnostic brain signatures of current and future weight

Understanding the neurobiological underpinnings of weight gain could reduce excess mortality and improve long-term trajectories of psychiatric disorders. Using brain scans from healthy individuals (<i>n</i> = 1,504), we trained a model to predict body mass index (BMI) and applied it to individuals with schizophrenia (<i>n</i> = 146), clinical high-risk states for psychosis (<i>n</i> = 213) and recent-onset depression (ROD, <i>n</i> = 200). We computed BMIgap (BMI<sub>predicted</sub> - BMI<sub>measured</sub>), interrogated its brain-level overlaps with schizophrenia and explored whether BMIgap predicted weight gain at the 1-year and 2-year follow-ups. Schizophrenia (BMIgap = 1.05 kg m<sup>-</sup> <sup>2</sup>) and clinical high-risk individuals (BMIgap = 0.51 kg m<sup>-</sup> <sup>2</sup>) showed increased BMIgap and individuals with ROD (BMIgap = -0.82 kg m<sup>-</sup> <sup>2</sup>) showed decreased BMIgap. Shared brain patterns of BMI and schizophrenia were linked to illness duration, disease onset and hospitalization frequency. Higher BMIgap predicted future weight gain, particularly in younger individuals with ROD, and at 2-year follow-up. Here we show that BMIgap can serve as a potential brain-derived measure to stratify at-risk individuals and deliver tailored interventions for better metabolic risk control.

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Journal
Nature Mental Health
Published
2025-10-20
DOI
https://doi.org/10.1038/s44220-025-00522-3
Primary Topic
Diet and metabolism studies
Type
article
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article

The BMIgap tool to quantify transdiagnostic brain signatures of current and future weight

Lars Tjelta Westlye, Alessandro Bertolino, Andreas Meyer‐Lindenberg, Mads L. Pedersen et al.
Nature Mental Health
Diet and metabolism studies
article

The BMIgap tool to quantify transdiagnostic brain signatures of current and future weight

Lars Tjelta Westlye, Alessandro Bertolino, Andreas Meyer‐Lindenberg, Mads L. Pedersen, Adyasha Khuntia, Emanuel Schwarz, Ole A. Andreassen, Stephen James Wood, Madalina-Octavia Buciuman, David Popovic, Rachel Upthegrove, Paolo Brambilla, Elif Sarisik, Raimo K. R. Salokangas, Jarmo A. Hietala, Stefan Borgwardt, Joseph Kambeitz, Nikolaos Koutsouleris, Rebekka Lencer, Eva Meisenzahl, Peter Falkai, Alexander J. Wiegand
article en

Abstract

Understanding the neurobiological underpinnings of weight gain could reduce excess mortality and improve long-term trajectories of psychiatric disorders. Using brain scans from healthy individuals (<i>n</i> = 1,504), we trained a model to predict body mass index (BMI) and applied it to individuals with schizophrenia (<i>n</i> = 146), clinical high-risk states for psychosis (<i>n</i> = 213) and recent-onset depression (ROD, <i>n</i> = 200). We computed BMIgap (BMI<sub>predicted</sub> - BMI<sub>measured</sub>), interrogated its brain-level overlaps with schizophrenia and explored whether BMIgap predicted weight gain at the 1-year and 2-year follow-ups. Schizophrenia (BMIgap = 1.05 kg m<sup>-</sup> <sup>2</sup>) and clinical high-risk individuals (BMIgap = 0.51 kg m<sup>-</sup> <sup>2</sup>) showed increased BMIgap and individuals with ROD (BMIgap = -0.82 kg m<sup>-</sup> <sup>2</sup>) showed decreased BMIgap. Shared brain patterns of BMI and schizophrenia were linked to illness duration, disease onset and hospitalization frequency. Higher BMIgap predicted future weight gain, particularly in younger individuals with ROD, and at 2-year follow-up. Here we show that BMIgap can serve as a potential brain-derived measure to stratify at-risk individuals and deliver tailored interventions for better metabolic risk control.

Nature Mental HealthVol. 3(11)
Oslo University Hospital (NO), University of Turku (FI), The University of Melbourne (AU), University of Cologne (DE), King's College London (GB), University of Oslo (NO), University of Basel (CH), University of Milan (IT), Heidelberg University (DE), University Hospital Heidelberg (DE), Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT), University of Oxford (GB), Orygen Youth Health (AU), Institute of Mental Health (GB), Central Institute of Mental Health (DE), Orygen (AU), German Center for Infection Research (DE), German Centre for Cardiovascular Research (DE), Max Planck Institute of Psychiatry (DE), Oxford BioMedica (United Kingdom) (GB), International Max Planck Research School for Advanced Methods in Process and Systems Engineering (DE), Birmingham Women’s and Children’s NHS Foundation Trust (GB), Heinrich Heine University Düsseldorf (DE), University of Bari Aldo Moro (IT), University of Birmingham (GB), Ludwig-Maximilians-Universität München (DE), University of Lübeck (DE)
Openalex Percentile: Top 63%
Diet and metabolism studies
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