Machine Learning Models Rank Predictive Risks For Alzheimer’s Disease

This study, published in the journal Scientific Reports, is the first to construct machine learning models with genetic risk scores, non-genetic information and electronic health record data from nearly half a million individuals to rank risk factors in order of how strong their association is with eventual development of Alzheimer’s disease. Results showed that age is the biggest risk factor for Alzheimer’s in the entire population, but for the older adults, genetic risk as determined by a polygenic risk score was more predictive. Additionally, a low household income also emerged as an important risk factor, ranking either third or fourth after the effects of age and genetics.