ArticleNeuroImage. Clinical2018
Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition.
Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.
- Linking Polygenic Risk of Schizophrenia to Variation in Magnetic Resonance Imaging Brain Measures: A Comprehensive Systematic Review.Schizophrenia bulletin · 2024Pooled it
- Brain controllability mediates the effects of early life adversity on adolescent behavior and cognition moderated by genetic risks.Research square · 2026Article
- Integration of estimated regional gene expression with neuroimaging and clinical phenotypes at biobank scale.PLoS biology · 2024Article
- Association of polygenic scores for autism with volumetric MRI phenotypes in cerebellum and brainstem in adults.Molecular autism · 2024Article
- The interaction effects of age, APOE and common environmental risk factors on human brain structure.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Associations between polygenic risk scores and accelerated brain ageing in smokers.Psychological medicine · 2023Article
- Association of polygenic risk for bipolar disorder with grey matter structure and white matter integrity in youth.Translational psychiatry · 2023Article
- Specificity of Psychiatric Polygenic Risk Scores and Their Effects on Associated Risk Phenotypes.Biological psychiatry global open science · 2023Article
- Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- The neural signatures of psychoses in Alzheimer's disease: a neuroimaging genetics approach.European archives of psychiatry and clinical neuroscience · 2023Article
- Individual prediction and classification of cognitive impairment in patients with white matter lesions based on gray matter volume.Annals of translational medicine · 2022Article
- Statistical testing in transcriptomic-neuroimaging studies: A how-to and evaluation of methods assessing spatial and gene specificity.Human brain mapping · 2022Article
- Improved Multiclassification of Schizophrenia Based on Xgboost and Information Fusion for Small Datasets.Computational and mathematical methods in medicine · 2022Article
- Patterns of brain asymmetry associated with polygenic risks for autism and schizophrenia implicate language and executive functions but not brain masculinization.Molecular psychiatry · 2021Article
- Spatially Covarying Patterns of Gray Matter Volume and Concentration Highlight Distinct Regions in Schizophrenia.Frontiers in neuroscience · 2021Article
- Multi-dimensional predictions of psychotic symptoms via machine learning.Human brain mapping · 2020Article
- Polygenic risk for autism spectrum disorder affects left amygdala activity and negative emotion in schizophrenia.Translational psychiatry · 2020Article
- Polygenic Risk Scores Shed Light on the Relationship between Schizophrenia and Cognitive Functioning: Review and Meta-Analysis.Journal of clinical medicine · 2020Article
- Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning.NeuroImage. Clinical · 2020Article
- Treatment-Resistant Schizophrenia: Insights From Genetic Studies and Machine Learning Approaches.Frontiers in pharmacology · 2019Review
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Psychiatric illnesses are complex and polygenic. They are associated with widespread alterations in the brain, which are partly influenced by genetic factors. There have been some attempts to relate polygenic risk scores (PRS) - a measure of the overall genetic risk an individual carries for a disorder - to brain structure using univariate methods. However, PRS are likely associated with distributed and covarying effects across the brain. We therefore used multivariate machine learning in this proof-of-principle study to investigate associations between brain structure and PRS for four psychiatric disorders; attention deficit-hyperactivity disorder (ADHD), autism, bipolar disorder and schizophrenia. The sample included 213 individuals comprising patients with depression (69), bipolar disorder (33), and healthy controls (111). The five psychiatric PRSs were calculated based on summary data from the Psychiatric Genomics Consortium. T1-weighted magnetic resonance images were obtained and voxel-based morphometry was implemented in SPM12. Multivariate relevance vector regression was implemented in the Pattern Recognition for Neuroimaging Toolbox (PRoNTo). Across the whole sample, a multivariate pattern of grey matter significantly predicted the PRS for autism (r = 0.20, p
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