Ann Neurol: Columbia University found that: genetic risk score can effectively predict Alzheimer's disease

At present, for patients with LOAD (late-onset AD) or LOAD-endophenotypes, efforts have been made in the development of Polygenic risk scores (PRSs), and good sensitivity and specificity have been achieved in detecting disease states.
Improved the diagnosis algorithm when the recognized variables such as gender, age and APOE are correlated
.

PRS uses summary statistics from a large GWAS work ("training" data set) to construct an informative predictor variable for the same result or related endogenous phenotype in an independent data set ("validation" data set)
.

In the autopsy cohort, CH-PRS alone reached AUC=72%, which increased to AUC=83% in the full model
.

In the replicating CH cohort, higher CH-PRS was significantly associated with clinical LOAD (OR=1.
61, 95%CI=1.
19-2.
17).
In longitudinal subsamples, CH-PRS was significantly predicted to be converted to LOAD (HR= 1.
93, CI=1.
70-2.
20)
.

The important significance of such research lies in the discovery: the rich diversity of genetic research is essential to provide effective PRS to analyze the LOAD risk of different populations
.