A novel age-informed approach for genetic association analysis in Alzheimer's disease.

ABSTRACT:

Background

Many Alzheimer's disease (AD) genetic association studies disregard age or incorrectly account for it, hampering variant discovery.

Methods

Using simulated data, we compared the statistical power of several models: logistic regression on AD diagnosis adjusted and not adjusted for age; linear regression on a score integrating case-control status and age; and multivariate Cox regression on age-at-onset. We applied these models to real exome-wide data of 11,127 sequenced individuals (54% cases) and replicated suggestive associations in 21,631 genotype-imputed individuals (51% cases).

Results

Modeling variable AD risk across age results in 5-10% statistical power gain compared to logistic regression without age adjustment, while incorrect age adjustment leads t

SUBMITTER: Le Guen Y 

PROVIDER: S-EPMC8017764 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature