| Title: | Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network |
| Journal: | Nature Communications |
| Published: | 22 Aug 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35995794/ |
| DOI: | https://doi.org/10.1038/s41467-022-32513-8 |
| URL: | https://www.nature.com/articles/s41467-022-32513-8.pdf |
| Citations: | 19 (17 in last 2 years) as of 8 Aug 2024 |
Publication 10449
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Abstract
Schizophrenia is a highly heritable psychiatric disorder characterized by widespread functional and structural brain abnormalities. However, previous association studies between MRI and polygenic risk were mostly ROI-based single modality analyses, rather than identifying brain-based multimodal predictive biomarkers. Based on schizophrenia polygenic risk scores (PRS) from healthy white people within the UK Biobank dataset (N = 22,459), we discovered a robust PRS-associated brain pattern with smaller gray matter volume and decreased functional activation in frontotemporal cortex, which distinguished schizophrenia from controls with >83% accuracy, and predicted cognition and symptoms across 4 independent schizophrenia cohorts. Further multi-disease comparisons demonstrated that these identified frontotemporal alterations were most severe in schizophrenia and schizo-affective patients, milder in bipolar disorder, and indistinguishable from controls in autism, depression and attention-deficit hyperactivity disorder. These findings indicate the potential of the identified PRS-associated multimodal frontotemporal network to serve as a trans-diagnostic gene intermediated brain biomarker specific to schizophrenia.</p>
16 Authors
- Shile Qi
- Jing Sui
- Godfrey Pearlson
- Juan Bustillo
- Nora I. Perrone-Bizzozero
- Peter Kochunov
- Jessica A. Turner
- Zening Fu
- Wei Shao
- Rongtao Jiang
- Xiao Yang
- Jingyu Liu
- Yuhui Du
- Jiayu Chen
- Daoqiang Zhang
- Vince D. Calhoun
1 Application
| Application ID | Title |
|---|---|
| 34175 | Identify biomarkers for distinguishing different mental disorders using brain images and their associations with genetic risk |
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