aceMetabolites stratify future major depressive disorder risk in obese population: a longitudinal machine learning analysis
Background Obesity is a well-established risk factor for major depressive disorder (MDD), yet the risk is not uniform, highlighting the need for precise risk stratification. This study aimed to develop a metabolomics-based prediction model to identify high-risk metabolic phenotypes among obese participants and to elucidate the causal metabolic pathways involved. Methods Forty-one-thousand-four-hundred-fifty-nine obese participants were followed for a median of 14.4 years. We integrated multiple machine learning…
A LightGBM model trained on metabolomic data predicted incident major depressive disorder among obese participants with AUCs around 0.82-0.84 over 3 to 9 years and outperformed existing clinical models.
Evidence
- Peer-reviewedPsychological Medicine2026-07-29
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Truvace Impact Record TRV-2026-0590, v1: “Metabolites stratify future major depressive disorder risk in obese population: a longitudinal machine learning analysis.” Truvace, 2026-07-30. /record/TRV-2026-0590 (accessed at citation time). sha256 c18a7d8de8484fa5…
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