Towards precision medicine in Alzheimer's disease: deciphering genetic data to establish informative biomarkers.

INTRODUCTION

Developing biomarker tools for identification of individuals at high-risk for late-onset Alzheimer's disease (LOAD) is important for prognosis and early treatment. This review focuses on genetic factors and their potential role for precision medicine in LOAD.

AREAS COVERED

e4 is the strongest genetic risk factor for non-Mendelian LOAD, and the -linkage disequilibrium (LD) region has produced the most significant association signal in multi-center genome-wide-association-studies (GWAS). Consideration of extended haplotypes in the -LD region and specifically, non-coding variants in putative enhancer elements, such as the -polyT, in-addition to the coding variants that comprise the -genotypes, may be useful for predicting subjects at high-risk of developing LOAD and estimating age-of-onset of early disease-stage symptoms. A genetic-biomarker based on -polyT haplotypes, and age is currently applied in a clinical trial for prevention/delay of LOAD onset. Additionally, we discuss LOAD-GWAS discoveries and the development of new genetic risk scores based on LOAD-GWAS findings other than the -LD region.

EXPERT COMMENTARY

Deciphering the precise causal genetic-variants within LOAD-GWAS regions will advance the development of genetic-biomarkers to complement and refine the -LD region based prediction model. Collectively, the genetic-biomarkers will be translational for early diagnosis and enrichment of clinical trials with subjects at high-risk.