Common variants in Alzheimer's disease and risk stratification by polygenic risk scores

Abstract

Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease.

Fig. 1. Flow chart of analysis steps.

Discovery meta-analysis in GR@ACE, IGAP stage 1 + 2 and UKBiobank followed by a replication in 16 independent cohorts. The genome-wide significant signals found in meta-GWAS were used to perform a Polygenic Risk Score in a clinical and pathological AD dataset. See Supplementary Methods to more information about the cohorts included and methods to the PRS generation. ^aExtended dataset (Moreno-Grau et al.), ^bStageI + StageII (Kunkle et al.), ^cBy proxy AD: Meta-analysis of maternal and paternal history of dementia (Marioni et al.), ^dExtra and independent GR@ACE dataset incorporated only for replication purposes, ^ePathologically confirmed AD cases, ^fAD cases diagnosed based on clinical criteria, ^gControls participants aged 55 years and younger. N = Total of individuals within specified data.

Fig. 2. GWAS meta-analysis for AD risk (N = 467,623).

a Manhattan plot of overall meta-analysis for genome-wide association in Alzheimer’s disease highlighting in pink the loci associated with AD in this study (PRKD3/NDUFAF7, SHARPIN, CHRNE, PLCG2, and APP). b–f Locus plots for the signals associated with AD in overall meta-analysis results.

Fig. 3. Genetic landscape for Alzheimer’s disease.

This figure shows the history of genetic discoveries in AD research over the past 30 years. This figure was constructed to our best knowledge of literature, but is not a systematic review of literature. For common variants, we selected only signals firmly replicated in large meta-GWAS (Lambert et al., Kunkle et al., Jun et al., Sims et al., Jansen et al. and present study). For rare variants, we only selected those variants widely replicated excluding those loci presenting conflicting results. Abbreviations and more information about the genes can be found in Supplementary Data 4. The risk alleles associated with AD were represented in orange and the protective alleles in blue. GWAS Genome-Wide Association Study, OR odds ratio.

Fig. 4. Polygenic risk scores for AD.

a The 39-SNP PRS association with clinical (OR = 1.30, 95% CI [1.18–1.44], p = 1.1 × 10⁻⁷) and pathologically confirmed AD cases (OR = 1.38, per 1-SD increase in the PRS, 95% CI [1.21–1.58], p = 1.5 × 10⁻⁶) from EADB–F.ACE/BBB dataset. b PRS association with AD in the presence of concomitant brain pathologies (besides AD). c PRS association with AD stratified by sex and AAO. A similar association of the PRS with AD was found in both sexes (OR_males = 1.33, [1.13–1.56], p = 5.8 × 10⁻⁴ vs. OR_females = 1.32, [1.19–1.47], p = 2.5 × 10⁻⁷). In (a–c) data are presented as Odds Ratio per 1-SD increase in PRS (95% CI). The generated PRS was validated using logistic regression adjusted by four principal components.

Fig. 5. Polygenic Risk Scores APOE stratification for AD in n = 12,386 biologically independent samples from GR@ACE/DEGESCO.

a The AD risk of PRS groups compared to those with the 2% lowest risk. The 2% highest risk had a 3.0-fold (95% CI [2.12–4.18], p = 3.2 × 10⁻¹⁰) increased risk compared with those with the 2% lowest risk. No interaction was found between the PRS and APOE genotypes (p value = 0.76). b The AD risk stratified by PRS and APOE risk groups compared to the lowest risk group (OR 95% CI). Association was found between highest and lowest-PRS percentiles within the APOE genotype groups: ɛ2ɛ2/ɛ2ɛ3 carriers (OR = 2.48 [1.51–4.08], p = 3.4 × 10⁻⁴), ɛ3ɛ3 carriers (OR = 2.67 [1.93–3.69], p = 3.5 × 10⁻⁹), ɛ2ɛ4/ɛ3ɛ4 carriers (OR = 2.47 [1.67–3.66], p = 6.8 × 10⁻⁶), and ɛ4ɛ4 carriers (OR = 2.02 [1.05–3.85], p = 3.4 × 10⁻²). Comparisons of the highest and lowest-PRS percentiles with respect to the APOE genotype groups: a difference was found between highest ɛ2ɛ2/ɛ2ɛ3 carriers vs. lowest ɛ3ɛ3 carriers (OR = 0.51 [0.34–0.75], p = 7.8 × 10⁻⁴), but not between highest ɛ3ɛ3 carriers vs. lowest ɛ2ɛ4/ɛ3ɛ4 carriers (OR = 1.17 [0.82–1.66], p = 0.40) and highest ɛ2ɛ4/ɛ3ɛ4 carriers vs. lowest ɛ4ɛ4 carriers (OR = 0.89 [0.52–1.53], p = 0.68). c The AAO of AD stratified by PRS and APOE risk groups. No difference in odds for AD was found between the PRS percentiles with AAO in APOE ɛ2ɛ2/ɛ2ɛ3 (lowest = 82 years, highest = 83 years, p_Wilcoxon = 0.39) and APOE ɛ3ɛ3 (lowest = 82 years, highest = 81 years, p = 0.16). However, a 4-year difference was found between APOE ɛ4 heterozygotes (p_Wilcoxon = 6.9 × 10⁻⁵, 81 years compared with 77 years) and 5.5 years difference (p_Wilcoxon = 4.6 × 10⁻⁵, 78.5 years compared with 73 years) in APOE ɛ4 homozygotes. Data are represented as boxplots as described in the manual of ggplot2 package in R. a–c Logistic regression models adjusted for four population ancestry components were used as statistical test. d Cox regression model on AAO. The determinants are the PRS and the APOE categories, a PRS*APOE interaction term and population substructure as covariates. The curve shows the probability a case in one of the eight groups has developed AD by a certain age (x-axis).