Towards cascading genetic risk in Alzheimer’s disease

Abstract

AbstractBackgroundAlzheimer’s disease (AD) typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: Amyloid (A), Tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, where each of the biomarkers can be either positive (+) or negative (-). Over the past decades genome wide association studies (GWAS) have implicated about 90 different loci involved with the development of late onset Alzheimer’s disease (LOAD). Here we investigate whether genetic risk for AD contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect.MethodsAmyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the AD Neuroimaging Initiative (ADNI) cohort. In 425 participants with biomarker-confirmed A-T-status, we employed Cox proportional hazards models to estimate the contribution ofAPOEand polygenic risk scores (PRS; beyondAPOE) to convert to A+T-status (68 conversions). Furthermore, we repeated the analysis in 402 participants with A+T-status and investigated the genetic contribution to conversion to A+T+ (46 conversions). Both survival analyses were adjusted for age, sex, and years of education.ResultsFor progression from A-T- to A+T-, APOE-e4 burden showed significant effect (HR=2.71; 95% CI: 1.65-4.45; P<0.001), while PRS did not (HR=1.06; 95% CI: 0.82-1.40; P=0.65). Conversely, for the transition from A+T- to A+T+, the APOE-e4 burden contribution was reduced (HR=1.65 95% CI: 1.05-2.59; P=0.030), while the PRS showed an increased contribution (HR=1.67; 95% CI:1.22-2.28; P=0.0014). The marginalAPOEeffect was driven by e4 homozygotes (HR=2.81; 95% CI: 1.14-6.91; P=0.025) as opposed to e4 heterozygotes (HR=1.5; 95% CI: 0.75-2.99; P=0.25).ConclusionThe genetic risk for LOAD unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of transition between ATN stages, a better understanding of the molecular processes leading to AD as well as opening therapeutic windows for targeted interventions.