Chaudhury S, et al. - Researchers sought to develop a polygenic risk score (PRS) model to predict late-onset Alzheimer’s disease (LOAD) diagnosis in the brains for dementia research (BDR) cohort. Using PRSice-2 and resulting from summary statistics from the International Genomics of Alzheimer’s Disease Project genome-wide association study, they created PRS for each individual. From the Southampton inflammation, cognition and stress study, a longitudinal sample of individuals with mild-cognitive impairment (MCI) was used to see if the model could predict those who went from MCI to LOAD. For conversion from MCI to LOAD, predictability of 61.0% was noted when applied to the MCI cohort. With one-way ANOVA, they noted increases in average PRS scores across the diagnosis group, suggesting that the groups were significantly different in PRS. There is possible utility of the PRS model for LOAD for recognizing those with MCI at risk of conversion to LOAD, according to this analysis.