The causal relationship between neuroimaging and Parkinson's disease: A two-sample Mendelian randomization study.
The causal relationship between neuroimaging and Parkinson's disease: A two-sample Mendelian randomization study.
Where did the research take place?
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Hengyang, CN · Author affiliation
Department of Electrocardiogram, The Second Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China.Location evidence
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Original abstract
Parkinson's disease (PD) is a neurodegenerative disorder whose etiology and progression remain not fully understood, posing significant challenges for both diagnosis and treatment. This study leverages the 2-sample Mendelian Randomization (TSMR) approach to systematically examine the possible causal connections involving neuroimaging characteristics and the risk of developing PD. Making use of genetic variations from extensive genome-wide association studies (GWAS) as instrumental factors, this analysis focuses on neuroimaging traits related to cortical and subcortical gray matter volumes. The primary findings reveal that specific changes in neuroimaging traits, notably in regions such as the right ventral diencephalon and the thalamus, have a strong causal connection with the risk of PD. These associations were robust across multiple MR methods, including MR-Egger, Inverse-Variance Weighted (IVW), and Weighted Median approaches, supplemented by extensive sensitivity analyses to guarantee the accuracy of the findings. Our research's insights into the structural and functional brain changes provide a deeper understanding of PD's etiology, suggesting that certain neuroimaging features may not only precede but also potentially drive the disease process. This underscores the possibility of these neuroimaging traits serving as early biomarkers or targets for preventive measures against PD. Despite its strengths in causal inference and the use of extensive GWAS datasets, limitations include reliance on data primarily from European populations and inherent assumptions of Mendelian Randomization.