Best Linear Unbiased Prediction of Individual Polygenic Susceptibility to Sporadic Vascular Dementia

Abstract

Genetic factors of sporadic vascular dementia have been quite limitedly understood. Many underlying polygenes are suspected to contribute to susceptibility to sporadic vascular dementia as a typical complex disease although they have not been identified from genome-wide association studies. This study suggests a stochastic prediction of individual polygenetic susceptibility to sporadic vascular dementia using best linear unbiased prediction in a mixed model framework. The prediction shows a relative degree of individual genetic susceptibility to the disease that reflects its integrative polygenetic factors across the genome. The estimate should take into account heritability and the prevalence of sporadic vascular dementia to cope with the disease. This offers a model for application of a genetic blueprint for a complex disease to personalized preventive medicine.