ArticleSchizophrenia research2021
White matter brain aging in relationship to schizophrenia and its cognitive deficit.
Article in Schizophrenia research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.
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Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- BrainAGE, brain health, and mental disorders: A systematic review.Neuroscience and biobehavioral reviews · 2024Pooled it
- Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium.Molecular psychiatry · 2023Pooled it
- Premature aging in serious mental illness.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Review
- Brain Age Disparities in Psychosis Across DSM Diagnoses and B-SNIP Biotypes.Schizophrenia bulletin · 2026Article
- The Retinal Age Gap as a Marker of Accelerated Aging in the Early Course of Schizophrenia.Schizophrenia bulletin · 2026Article
- Dementia in older adults with schizophrenia: a 12-year analysis of prevalence, incidence, and treatment patterns in South Korea.Schizophrenia (Heidelberg, Germany) · 2025Article
- Dynamic Brain Age Modeling Identifies Network-Specific Cognitive Deficits in Schizophrenia.Research square · 2025Article
- Driving Performance in Schizophrenia: The Role of Neurocognitive Correlates-A Systematic Review.Brain sciences · 2025Review
- Functional Brain Age Acceleration from Dynamic and Static Connectivity Predicts Working Memory and Attention Deficits in Schizophrenia.medRxiv : the preprint server for health sciences · 2025Article
- Article
- Human immunodeficiency virus accelerates brain aging and disrupts the trajectory of glymphatic clearance in aging brain.Frontiers in psychiatry · 2025Article
- White matter brain-age in diverse forms of epilepsy and interictal psychosis.Scientific reports · 2024Article
- Deep Learning-based Brain Age Prediction in Patients With Schizophrenia Spectrum Disorders.Schizophrenia bulletin · 2024Article
- Relative brain age is associated with socioeconomic status and anxiety/depression problems in youth.Developmental psychology · 2024Article
- Illness-related variables and abnormalities of resting-state brain activity in schizophrenia.Frontiers in psychiatry · 2024Article
- Geroscience-Centric Perspective for Geriatric Psychiatry: Integrating Aging Biology With Geriatric Mental Health Research.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2024Review
- Evaluating the causal effect of tobacco smoking on white matter brain aging: a two-sample Mendelian randomization analysis in UK Biobank.Addiction (Abingdon, England) · 2023Article
- 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
- Schizophrenia as metabolic disease. What are the causes?Metabolic brain disease · 2023Review
- Predicting aging trajectories of decline in brain volume, cortical thickness and fractional anisotropy in schizophrenia.Schizophrenia (Heidelberg, Germany) · 2023Article
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Authors and funding
13 authors.
Funding
Abstract
We hypothesized that cerebral white matter deficits in schizophrenia (SZ) are driven in part by accelerated white matter aging and are associated with cognitive deficits. We used a machine learning model to predict individual age from diffusion tensor imaging features and calculated the delta age (Δage) as the difference between predicted and chronological age. Through this approach, we translated multivariate white matter imaging features into an age-scaled metric and used it to test the temporal trends of accelerated aging-related white matter deficit in SZ and its association with the cognition. A feature selection procedure was first employed to choose fractional anisotropy values in 34 of 43 white fiber tracts. Using these features, a machine learning model was trained based on a training set consisted of 107 healthy controls (HC). The brain age of 166 SZs and 107 HCs in the testing set were calculated using this model. Then, we examined the SZ-HC group effect on Δage and whether this effect was moderated by chronological age using the regression spline model. The results showed that Δage was significantly elevated in the age > 30 group in patients (p < 0.001) but not in age ≤ 30 group (p = 0.364). Δage in patients was significantly and negatively associated with both working memory (β = -0.176, p = 0.007) and processing speed (β = -0.519, p = 0.035) while adjusting sex and chronological age. Overall, these findings indicate that the Δage is elevated in SZs and become significantly from the third decade of life; the increase of Δage in SZs is associated with the declined neurocognitive performance.
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