ArticleNeuroImage. Clinical2022
Detection of advanced brain aging in schizophrenia and its structural underpinning by using normative brain age metrics.
Article in NeuroImage. Clinical, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.
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Who cites it
21 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Neuroimaging Insights into the Public Health Burden of Neuropsychiatric Disorders: A Systematic Review of Electroencephalography-Based Cognitive Biomarkers.Medicina (Kaunas, Lithuania) · 2025Pooled it
- Magnetic resonance imaging-based machine learning classification of schizophrenia spectrum disorders: a meta-analysis.Psychiatry and clinical neurosciences · 2024Pooled it
- BrainAGE, brain health, and mental disorders: A systematic review.Neuroscience and biobehavioral reviews · 2024Pooled it
- Differential cerebral white matter tract alterations in generalized anxiety disorder revealed by ultra-high-field 7 T diffusion-weighted imaging.Journal of affective disorders · 2026Article
- Divergent Multimodal Age-Association Profiles Across the Human Brain.Nature communications · 2026Article
- Deficits in Emotional Face Processing Indexed by N170 Modulation in Chronic and in First Hospitalized Schizophrenia.Clinical EEG and neuroscience · 2026Article
- Normative age-related structural brain deviations underlying psychopathology, cognitive impairment and neurological soft signs in schizophrenia spectrum disorders.Translational psychiatry · 2026Article
- MDFNet: a multi-dimensional feature fusion model based on structural magnetic resonance imaging representations for brain age estimation.Magma (New York, N.Y.) · 2026Article
- The Retinal Age Gap as a Marker of Accelerated Aging in the Early Course of Schizophrenia.Schizophrenia bulletin · 2026Article
- Cortical GABAergic Neuron Dysregulation in Schizophrenia Is Age Dependent.Biological psychiatry global open science · 2026Article
- Differential Cerebral White Matter Tract Alterations in Generalized Anxiety Disorder Revealed by Ultra-High Field 7T Diffusion-Weighted Imaging.bioRxiv : the preprint server for biology · 2025Article
- Brain-age models with lower age prediction accuracy have higher sensitivity for disease detection.PLoS biology · 2025Article
- Resting-state functional connectivity correlates of brain structural aging in schizophrenia.European archives of psychiatry and clinical neuroscience · 2025Article
- A multimodal ensemble stacking model improves brain age prediction and reveals associations with schizophrenia symptoms.Frontiers in psychiatry · 2025Article
- Brain Age Gap in Early Illness Schizophrenia and the Clinical High-Risk Syndrome: Associations With Experiential Negative Symptoms and Conversion to Psychosis.Schizophrenia bulletin · 2024Article
- Deep Learning-based Brain Age Prediction in Patients With Schizophrenia Spectrum Disorders.Schizophrenia bulletin · 2024Article
- Advanced brain aging in Parkinson's disease with cognitive impairment.NPJ Parkinson's disease · 2024Article
- Superpixel-ComBat modeling: A joint approach for harmonization and characterization of inter-scanner variability in T1-weighted images.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- 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
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12 authors.
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Abstract
Conceptualizing mental disorders as deviations from normative functioning provides a statistical perspective for understanding the individual heterogeneity underlying psychiatric disorders. To broaden the understanding of the idiosyncrasy of brain aging in schizophrenia, we introduced an imaging-derived brain age paradigm combined with normative modeling as novel brain age metrics. We constructed brain age models based on GM, WM, and their combination (multimodality) features of 482 normal participants. The normalized predicted age difference (nPAD) was estimated in 147 individuals with schizophrenia and their 130 demographically matched controls through normative models of brain age metrics and compared between the groups. Regression analyses were also performed to investigate the associations of nPAD with illness duration, onset age, symptom severity, and intelligence quotient. Finally, regional contributions to advanced brain aging in schizophrenia were investigated. The results showed that the individuals exhibited significantly higher nPAD (P < 0.001), indicating advanced normative brain age than the normal controls in GM, WM, and multimodality models. The nPAD measure based on WM was positively associated with the negative symptom score (P = 0.009), and negatively associated with the intelligence quotient (P = 0.039) and onset age (P = 0.006). The imaging features that contributed to nPAD mostly involved the prefrontal, temporal, and parietal lobes, especially the precuneus and uncinate fasciculus. This study demonstrates that normative brain age metrics could detect advanced brain aging and associated clinical and neuroanatomical features in schizophrenia. The proposed nPAD measures may be useful to investigate aberrant brain aging in mental disorders and their brain-phenotype relationships.
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