Genomic Prediction and its Association with the Development of Dementia disease in the Elderly

Dementia is a severe neurological disorder involving complex interactions between various genetic and environmental factors. This paper explores the association between genomic prediction and the development of dementia in the elderly. Through a systematic review of existing research, the study delves into genomics, the genetic basis of dementia, and the etiology related to the genome. The research further examines the methods and applications of genomic prediction, focusing on the use of polygenic risk scores and machine learning algorithms in dementia studies. Through case analyses of large-scale genomic studies, key genes associated with dementia, such as Alzheimer's disease, are revealed. Additionally, the paper thoroughly analyzes the major findings of existing research, emphasizing the filling of knowledge gaps and the provision of new insights. Finally, the paper discusses the challenges faced by genomic prediction, including methodological difficulties, challenges in data interpretation, ethical and privacy concerns, and more. Looking ahead to future research directions, the paper highlights the establishment of personalized genomic prediction models, the application of new technologies, and the potential value of genomic prediction in early diagnosis and prevention of dementia.