ArticleFrontiers in aging neuroscience2022
Multimodal Magnetic Resonance Imaging Reveals Aberrant Brain Age Trajectory During Youth in Schizophrenia Patients.
Article in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- Disentangling individual heterogeneity reveals robust network and molecular signatures of major depressive disorder with suicidal ideation.Translational psychiatry · 2026Article
- The Retinal Age Gap as a Marker of Accelerated Aging in the Early Course of Schizophrenia.Schizophrenia bulletin · 2026Article
- Schizophrenia and Neurodevelopment: Insights From Connectome Perspective.Schizophrenia bulletin · 2025Review
- A multimodal ensemble stacking model improves brain age prediction and reveals associations with schizophrenia symptoms.Frontiers in psychiatry · 2025Article
- Article
- Immunophenotypes in psychosis: is it a premature inflamm-aging disorder?Molecular psychiatry · 2024Review
- A systematic review of multimodal brain age studies: Uncovering a divergence between model accuracy and utility.Patterns (New York, N.Y.) · 2023Review
- Investigating brain aging trajectory deviations in different brain regions of individuals with schizophrenia using multimodal magnetic resonance imaging and brain-age prediction: a multicenter study.Translational psychiatry · 2023Article
- Predicting aging trajectories of decline in brain volume, cortical thickness and fractional anisotropy in schizophrenia.Schizophrenia (Heidelberg, Germany) · 2023Article
- Discriminative analysis of schizophrenia patients using graph convolutional networks: A combined multimodal MRI and connectomics analysis.Frontiers in neuroscience · 2023Article
- Subjective Overview of Accelerated Aging in Schizophrenia.International journal of environmental research and public health · 2022Review
Corrections and comments
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Authors and funding
14 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accelerated brain aging had been widely reported in patients with schizophrenia (SZ). However, brain aging trajectories in SZ patients have not been well-documented using three-modal magnetic resonance imaging (MRI) data. In this study, 138 schizophrenia patients and 205 normal controls aged 20-60 were included and multimodal MRI data were acquired for each individual, including structural MRI, resting state-functional MRI and diffusion tensor imaging. The brain age of each participant was estimated by features extracted from multimodal MRI data using linear multiple regression. The correlation between the brain age gap and chronological age in SZ patients was best fitted by a positive quadratic curve with a peak chronological age of 47.33 years. We used the peak to divide the subjects into a youth group and a middle age group. In the normal controls, brain age matched chronological age well for both the youth and middle age groups, but this was not the case for schizophrenia patients. More importantly, schizophrenia patients exhibited increased brain age in the youth group but not in the middle age group. In this study, we aimed to investigate brain aging trajectories in SZ patients using multimodal MRI data and revealed an aberrant brain age trajectory in young schizophrenia patients, providing new insights into the pathophysiological mechanisms of schizophrenia.
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