A novel age‐informed approach for genetic association analysis in Alzheimer's disease. (December 2021)

• Record Type: Journal Article
• Authors: Guen, Yann Le; Belloy, Michael E; Napolioni, Valerio; Eger, Sarah J; Kennedy, Gabriel; Tao, Ran; He, Zihuai; Greicius, Michael D
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 3
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.050541
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: The increased risk of Alzheimer's Disease (AD) with age is well established. However, genome‐wide association studies of AD have often wrongly accounted for this known effect by covarying by age using age‐at‐onset for cases and age‐at‐last‐exam for controls. In most scenarios, this leads to controls being on average older than cases and the regression model incorrectly infers that age decreases AD risk. 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) (Table 1). Results: Modelling variable AD risk across age results in 10‐20% statistical power gain compared to logistic regression without age adjustment, while incorrect age adjustment leads to critical power loss (Figure 1). Applying our novel AD‐age score and/or Cox regression, we discovered and replicated novel variants associated with AD on KIF21B, USH2A, RAB10, RIN3 and TAOK2 genes (Figure 2, Tables 2, 3). Conclusion: Incorrect age adjustment may remain unnoticed when the age difference between cases/controls is small and when the sample size is sufficient to identify causal variants with adequate statistical power. If the age difference is large, however, as in the whole‐exome sequencing of the ADSP for which controls are 10 years older than cases, then it is highly detrimental to adjust by age. Here we have proposed a novel AD‐age score to correctly integrate the age information in the phenotype and showed that it led to a gain in statistical power compared to a traditional logistic regression without age adjustment.