{"title":"Major depressive disorder on a neuromorphic continuum","authors":"Jiao Li, Zhiliang Long, Gong-Jun Ji, Shaoqiang Han, Yuan Chen, Guanqun Yao, Yong Xu, Kerang Zhang, Yong Zhang, Jingliang Cheng, Kai Wang, Huafu Chen, Wei Liao","doi":"10.1038/s41467-025-57682-0","DOIUrl":null,"url":null,"abstract":"<p>The heterogeneity of major depressive disorder (MDD) has hindered clinical translation and neuromarker identification. Biotyping facilitates solving the problems of heterogeneity, by dissecting MDD patients into discrete subgroups. However, interindividual variations suggest that depression may be conceptualized as a “continuum,” rather than as a “category.” We use a Bayesian model to decompose structural MRI features of MDD patients from a multisite cross-sectional cohort into three latent disease factors (spatial pattern) and continuum factor compositions (individual expression). The disease factors are associated with distinct neurotransmitter receptors/transporters obtained from open PET sources. Increases cortical thickness in sensory and decreases in orbitofrontal cortices (Factor 1) associate with norepinephrine and 5-HT<sub>2A</sub> density, decreases in the cingulo-opercular network and subcortex (Factor 2) associate with norepinephrine and 5-HTT density, and increases in social and affective brain systems (Factor 3) relate to 5-HTT density. Disease factor patterns can also be used to predict depressive symptom improvement in patients from the longitudinal cohort. Moreover, individual factor expressions in MDD are stable over time in a longitudinal cohort, with differentially expressed disease controls from a transdiagnostic cohort. Collectively, our data-driven disease factors reveal that patients with MDD organize along continuous dimensions that affect distinct sets of regions.</p>","PeriodicalId":19066,"journal":{"name":"Nature Communications","volume":"147 1","pages":""},"PeriodicalIF":15.7000,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Communications","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41467-025-57682-0","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The heterogeneity of major depressive disorder (MDD) has hindered clinical translation and neuromarker identification. Biotyping facilitates solving the problems of heterogeneity, by dissecting MDD patients into discrete subgroups. However, interindividual variations suggest that depression may be conceptualized as a “continuum,” rather than as a “category.” We use a Bayesian model to decompose structural MRI features of MDD patients from a multisite cross-sectional cohort into three latent disease factors (spatial pattern) and continuum factor compositions (individual expression). The disease factors are associated with distinct neurotransmitter receptors/transporters obtained from open PET sources. Increases cortical thickness in sensory and decreases in orbitofrontal cortices (Factor 1) associate with norepinephrine and 5-HT2A density, decreases in the cingulo-opercular network and subcortex (Factor 2) associate with norepinephrine and 5-HTT density, and increases in social and affective brain systems (Factor 3) relate to 5-HTT density. Disease factor patterns can also be used to predict depressive symptom improvement in patients from the longitudinal cohort. Moreover, individual factor expressions in MDD are stable over time in a longitudinal cohort, with differentially expressed disease controls from a transdiagnostic cohort. Collectively, our data-driven disease factors reveal that patients with MDD organize along continuous dimensions that affect distinct sets of regions.
期刊介绍:
Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.