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Impact of cognition-related single nucleotide polymorphisms on brain imaging phenotype in Parkinson’s disease

Neural Regeneration Research 2023年第5期18卷 1154-1160页

作者： Ting Shen Jia-Li Pu Ya-Si Jiang Yu-Mei Yue Ting-Ting He Bo-Yi Qu Shuai Zhao Ya-Ping Yan Hsin-Yi Lai Bao-Rong Zhang Department of Neurology of the Second Affiliated Hospital Zhejiang University School of MedicineZhejiang UniversityHangzhouZhejiang ProvinceChina Department of Neurology of the Second Affiliated Hospital Interdisciplinary Institute of Neuroscience and TechnologyKey Laboratory of Medical Neurobiology of Zhejiang ProvinceZhejiang University School of MedicineHangzhouZhejiang ProvinceChina Department of Neurology of Sir Run Run Shaw Hospital Zhejiang University School of MedicineZhejiang UniversityHangzhouZhejiang ProvinceChina College of Biomedical Engineering and Instrument Science Key Laboratory for Biomedical Engineering of Ministry of EducationZhejiang UniversityHangzhouZhejiang ProvinceChina

Multiple single nucleotide polymorphisms may contribute to cognitive decline in Parkinson’s disease. However, the mechanism by which these single nucleotide polymorphisms modify brain imaging phenotype remains unclear. The aim of this study was to investigate the potential effects of multiple single nucleotide polymorphisms on brain imaging phenotype in Parkinson’s disease. Forty-eight Parkinson’s disease patients and 39 matched healthy controls underwent genotyping and 7 T magnetic resonance imaging. A cognitive-weighted polygenic risk score model was designed, in which the effect sizes were determined individually for 36 single nucleotide polymorphisms. The correlations between polygenic risk score, neuroimaging features, and clinical data were analyzed. Furthermore, individual single nucleotide polymorphism analysis was performed to explore the main effects of genotypes and their interactive effects with Parkinson’s disease diagnosis. We found that, in Parkinson’s disease, the polygenic risk score was correlated with the neural activity of the hippocampus, parahippocampus, and fusiform gyrus, and with hippocampal-prefrontal and fusiform-temporal connectivity, as well as with gray matter alterations in the orbitofrontal cortex. In addition, we found that single nucleotide polymorphisms in α-synuclein(SNCA) were associated with white matter microstructural changes in the superior corona radiata, corpus callosum, and external capsule. A single nucleotide polymorphism in catechol-O-methyltransferase was associated with the neural activities of the lingual, fusiform, and occipital gyri, which are involved in visual cognitive dysfunction. Furthermore, DRD3 was associated with frontal and temporal lobe function and structure. In conclusion, imaging genetics is useful for providing a better understanding of the genetic pathways involved in the pathophysiologic processes underlying Parkinson’s disease. This study provides evidence of an association between genetic factors, cognitive functions, and multi-modality neuroi

关键词： cognition imaging genetics magnetic resonance imaging multi-modality Parkinson’s disease polygenic risk score single nucleotide polymorphism ultra-high field

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maging genetics -towards discovery neuroscience

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Frontiers of Electrical and Electronic Engineering in China 2013年第4期8卷 227-245页

作者： Tian Ge Gunter Schumann Jianfeng Feng Centre for Computational Systems Biology School of Mathematical Sciences Fudan University Shanghai 200433 China Department of Computer Science University of Warwick Coventry CV4 7AL UK Institute of Psychiatry King's College London London WC2R 2LS UK

imaging genetics is an emerging field aimed at identifying and characterizing genetic variants that influence measures derived from anatomical or functional brain images, which are in turn related to brain-related illnesses or fundamental cognitive, emotional and behavioral processes, and are affected by environmental factors. Here we review the recent evolution of statistical approaches and outstanding challenges in imaging genetics, with a focus on population-based imaging genetic association studies. We show the trend in imaging genetics from candidate approaches to pure discovery science, and from univariate to multivariate analyses. We also discuss future directions and prospects of imaging genetics for ultimately helping understand the genetic and environmental underpinnings of various neuropsychiatric disorders and turning basic science into clinical strategies.

关键词： imaging genetics association study multiple testing 5-O approach

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