Biomarker‐based polygenic risk scores for profiling genetic susceptibility in Alzheimer's disease

Abstract

AbstractBackgroundPrecision medicine is designed to resolve heterogeneity in complex diseases such as Alzheimer’s (AD) to deliver timely and tailored treatment. Using ADNI data, we developed endophenotype‐specific polygenic risk scores (PRS) to assess the AD risk and to identify distinct genetic risk profiles among the converters.MethodWe used ADNI genetic, clinical and biomarker data for PRS development. We derived four ADRD endophenotype components including Amyloid (A), Tau (T), Neurodegeneration (N) and Vascular (V), by applying PCA on 11 phenotypic variables. Four individual biomarker PRSs (A, T, N, V) were obtained and combined into a single PRS (PRSATNV). Penalized regression (Lasso) applied for SNP selection and weight re‐estimation. Bootstrapping was used to minimize possible overfitting. On the ADNI test set, after removing participants with mild cognitive impairment (MCI), we estimated the odds and hazard of AD among the extreme PRSATNV quartiles (Q1,Q4). To identify biomarker‐specific genetic risk profiles among LMCI/AD participants, we performed K‐means clustering using the 4 biomarker PRSs (PRSA, PRST, PRSN, PRSV). Clustering was done based on APOE groups.ResultThe odds for AD individuals in the Q4 of PRSATNV was double those in Q1 (p=2.2e‐06, AUC=80%). On the same participants, we obtained a significant difference of 5 years in the AD onset between Q1 and Q4 (HR=2.2, p=6.9e‐03). Clustering restricted to LMCI/AD yielded 2 PRS clusters for ε3/ ε3 and ε3/ ε4 and 3 for ε4/ ε4 (Figure 1). In general, genetic risk profiles differed among the clusters for all APOE groups (PRSATNV in Table 1). The main difference was amyloid‐related for ε3/ ε3 carriers, neurodegeneration‐related for ε3/ ε4 and tau‐related for ε4/ ε4 (Table 1).ConclusionThe combined biomarker PRS we developed successfully identified individuals in high risk for AD. Using clusters derived from endophenotype‐specific genetic information we were able to identify distinct biomarker‐related genetic profiles among converters. Endophenotype‐based PRS may be useful for risk stratification and development of genetically tailored therapeutics as different mechanisms may contribute to AD onset for a given individual. Validation in independent samples is a critical next step.