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Magnetic resonance imaging (MRI) has been recognized as a valuable tool for achieving 'reification of clinical diagnosis' of major depressive disorder (MDD). However, the reliability and validity of MRI results are often compromised by genetic, environmental, and clinical heterogeneity within test samples. Here, we combined MRI with other clinical findings using multimodal MRI fusion algorithm to construct a data-driven, bottom-up diagnostic approach. The covariation patterns between the multimodal MRI features and differential expression of exosomal microRNA (miRNA) were identified on a subset of 70 MDD patients and 71 healthy controls (HCs) (served as a training set) as classification features, whereas data from the other 45 MDD patients and 43 HCs served as a test set. Furthermore, longitudinal data from 28 MDD patients undergoing antidepressant treatment for six months were utilized to validate the identified biomarkers, and related signaling pathways were initially explored in depression-like mice. Plasma exosome-derived miR-151a-3p levels were found to be significantly lower in MDD patients compared to HCs and correlated with abnormal changes in functional MRI (fMRI) metrics in the anterior cingulate cortex (ACC), visual cortex, and default mode network, etc. Then, these multimodal MRI features associated with miR-151a-3p expression distinguished MDD patients from HCs with high classification accuracy of 92.05% in support vector machine (SVM) model, outperforming the diagnostic rate when only multimodal MRI features with intergroup differences were entered (70.45%). Furthermore, 10 out of 28 MDD patients exhibited a clinically significant response to the treatment (a reduction of over 50% in Hamilton Rating Scale for Depression (HAMD) score). The significant upregulation of plasma exosomal miR-151a-3p levels and changes of fMRI indicators were also observed in these 10 patients after treatment of six months. Animal experiments have shown that reducing the expression of miR-151-3p in ACC induces depression-like behaviors in mice, while elevating hsa-miR-151a-3p expression in ACC alleviates the depression-like behaviors of mice exposed to chronic unpredictable mild stress. Our study proposed an innovative diagnostic model of MDD by combining the plasma exosome-derived miR-151a-3p expression with its associated multimodal MRI patterns, potentially serving as a novel diagnostic tool.
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http://dx.doi.org/10.1038/s41380-025-03102-0 | DOI Listing |
Neuro Endocrinol Lett
September 2025
Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China.
Background: Major depressive disorder (MDD) is associated with neuro-immune - metabolic - oxidative (NIMETOX) pathways.
Aims: To examine the connections among NIMETOX pathways in outpatient MDD (OMDD) with and without metabolic syndrome (MetS); and to determine the prevalence of NIMETOX aberrations in a cohort of OMDD patients.
Methods: We included 67 healthy controls and 66 OMDD patients and we assessed various NIMETOX pathways.
Trends Psychiatry Psychother
September 2025
Laboratory of Hormone Measurement, Department of Physiology and Behavior, Federal University of Rio Grande do Norte, Natal, Brazil. Postgraduate Program in Psychobiology, Center for Biosciences, Federal University of Rio Grande do Norte, Natal, Brazil. National Institute of Science and Technology fo
Background: Major Depressive Disorder (MDD) is a leading cause of global disability, contributing to substantial individual, social, and economic burdens. While antidepressant therapy remains the cornerstone of treatment, complementary lifestyle-based interventions, such as multimodal exercise and mindfulness, have shown promise in alleviating mood symptoms. However, their specific impact on sleep quality, a critical therapeutic target in MDD, remains underexplored.
View Article and Find Full Text PDFMetab Brain Dis
September 2025
Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277, Jiefang Avenue, Wuhan, Hubei, 430022, China.
Major depression disorder (MDD) is a mental condition that significantly threatens both physical and psychological health. This study aimed to discern variances in plasma metabolic profiles between MDD sufferers and healthy counterparts. Additionally, we tracked the hospitalization journey of MDD patients to investigate the normalization of metabolic irregularities through conventional treatment in the form of self-control.
View Article and Find Full Text PDFFront Nutr
August 2025
Faculty of Medicine, Department of Psychiatry, Medical University of Gdańsk, Gdańsk, Poland.
Unlabelled: Mood disorders, including major depressive disorder (MDD) and bipolar disorder (BP), significantly impact global health, with MDD affecting over 300 million people and BP affecting approximately 2% of the world's population. Ketamine, originally an anesthetic, has emerged as a promising treatment for patients with treatment-resistant depression (TRD), due to its unique pharmacological properties, such as N-methyl-D-aspartate (NMDA) receptor antagonism and anti-inflammatory effects. The potential of ketamine in treating depression has sparked debate regarding its effects on appetite.
View Article and Find Full Text PDFAlpha Psychiatry
August 2025
Information Sciences and Technology, George Mason University, Fairfax, VA 22030, USA.
Background: Herein, we report on the initial development, progress, and future plans for an autonomous artificial intelligence (AI) system designed to manage major depressive disorder (MDD). The system is a web-based, patient-facing conversational AI that collects medical history, provides presumed diagnosis, recommends treatment, and coordinates care for patients with MDD.
Methods: The system includes seven components, five of which are complete and two are in development.