Systematic metabolic characterization of mental disorders reveals age‐related metabolic disturbances as potential risk factors for depression in older adults. Issue 4 (30th September 2022)

• Record Type: Journal Article
• Authors: Liu, Yu; Zhao, Wanyu; Lu, Ying; Zhao, Yunli; Zhang, Yan; Dai, Miao; Hai, Shan; Ge, Ning; Zhang, Shuting; Huang, Mingjin; Liu, Xiaohui; Li, Shuangqing; Yue, Jirong; Lei, Peng; Dong, Biao; Dai, Lunzhi; Dong, Birong
• Is Part Of: MedComm. Volume 3:Issue 4(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-09-30
• Subjects: aging -- mental illness -- metabolomics -- lipidomics -- molecular classification; 610
• DOI: 10.1002/mco2.165
• Languages: English
• ISSNs: 2688-2663

Abstract

Abstract: Mental disorders are associated with dysregulated metabolism, but comprehensive investigations of their metabolic similarities and differences and their clinical relevance are few. Here, based on the plasma metabolome and lipidome of subcohort1, comprising 100 healthy participants, 55 cases with anxiety, 52 persons with depression, and 41 individuals with comorbidity, which are from WCHAT, a perspective cohort study of community‐dwelling older adults aged over 50, multiple metabolites as potential risk factors of mental disorders were identified. Furthermore, participants with mental illnesses were classified into three subtypes (S1, S2, and S3) by unsupervised classification with lipidomic data. Among them, S1 showed higher triacylglycerol and lower sphingomyelin, while S2 displayed opposite features. The metabolic profile of S3 was like that of the normal group. Compared with S3, individuals in S1 and S2 had worse quality of life, and suffered more from sleep and cognitive disorders. Notably, an assessment of 6, 467 individuals from the WCHAT showed an age‐related increase in the incidence of depression. Seventeen depression‐related metabolites were significantly correlated with age, which were validated in an independent subcohort2. Collectively, this work highlights the clinical relevance of metabolic perturbation in mental disorders, and age‐related metabolic disturbances may be a bridge‐linking aging and depressive. Abstract : Based on plasma metabolomics and lipidomics, we identified numerous potential risk factors for older adults with anxiety, depression, or comorbid anxiety‐depressive symptoms. Molecular classification revealed the clinical relevance of metabolic perturbations associated with these mental disorders. In addition, the incidence of depression increases with age. We revealed that the changes of depression‐related metabolites were significantly correlated with age, indicating the interplay among age, metabolic disturbances, and depression.