Abstract
Objective: This study aimed to explore the causal links between various lifestyle, demographic, cognitive factors and neurodegenerative diseases, and to develop an Alzheimer's disease (AD) risk prediction model.
Methods: Mendelian randomization analysis was conducted using genetic variants as instrumental variables to investigate the relationships between lifestyle, demographics, cognitive factors, and neurodegenerative diseases. We used the MR-Egger regression, weighted median method, Inverse Variance Weighting (IVW), and weighted model. Based on the Mendelian analysis results, logistic multivariate analysis was used for validation and to design an AD rating prediction model.
Results: Mendelian randomization analysis showed that beer intake was positively correlated with AD risk, whereas education level and cognitive ability were negatively correlated with AD risk. There was a positive correlation between education level, economic status, and risk of Parkinson's. There was a positive correlation between physical activity level and the risk of developing amyotrophic lateral sclerosis, and higher education level is significantly associated with a reduced risk of ALS. Logistic regression analysis showed that age and sex were positively correlated with AD, while education level was negatively correlated with AD. The accuracy of the AD risk prediction model was 78%, which was better than that of the logical model 62%.
Conclusion: Mendelian analysis results indicated that there is a causal relationship between beer intake, educational level, cognitive ability and AD. There is a causal relationship between education level, economic status, and Parkinson's disease. There was a causal relationship between physical activity level, education level, and amyotrophic lateral sclerosis. No causal relationship was found between these factors and Lewy body dementia or frontotemporal dementia. The rating prediction model outperformed traditional logistic models in terms of accuracy .