Common variants in Alzheimer’s disease: Novel association of six genetic variants with AD and risk stratification by polygenic risk scores
Authors: de Rojas Itziar , Moreno-Grau Sonia , Tesi Niccolò , Grenier-Boley Benjamin , Andrade Victor , Jansen Iris , Pedersen Nancy L. , Stringa Najada , Zettergren Anna , Hernández Isabel , Montrreal Laura , Antúnez Carmen , Antonell Anna , Tankard Rick M. , Bis Joshua C. , Sims Rebecca , Bellenguez Céline , Quintela Inés , González-Perez Antonio , Calero Miguel , Franco Emilio , Macías Juan , Blesa Rafael , Menéndez-González Manuel , Frank-García Ana , Luís Royo Jose , Moreno Fermín , Huerto Raquel , Baquero Miquel , Diez-Fairen Mónica , Lage Carmen , Garcia-Madrona Sebastian , García Pablo , Alarcón-Martín Emilio , Valero Sergi , Sotolongo-Grau Oscar ,   EADB, GR@ACE, DEGESCO, IGAP (ADGC, CHARGE, EADI, GERAD) and PGC-ALZ Consortia, Garcia-Ribas Guillermo , Sánchez-Juan Pascual , Pastor Pau , Pérez-Tur Jordi , Piñol-Ripoll Gerard , de Munain Adolfo Lopez , García-Alberca Jose María , Bullido María J. , Álvarez Victoria , Lleó Alberto , Real Luis M. , Mir Pablo , Medina Miguel , Scheltens Philip , Holstege Henne , Marquié Marta , Sáez María Eugenia , Carracedo Ángel , Amouyel Philippe , Williams Julie , Seshadri Sudha , van Duijn Cornelia M. , Mather Karen A. , Sánchez-Valle Raquel , Serrano-Ríos Manuel , Orellana Adelina , Tárraga Lluís , Blennow Kaj , Huisman Martijn , Andreassen Ole A. , Posthuma Danielle , Clarimón Jordi , Boada Mercè , van der Flier Wiesje M. , Ramirez Alfredo , Lambert Jean-Charles , van der Lee Sven J. , Ruiz Agustín 
Published: November 2019

BACKGROUND

Disentangling the genetic constellation underlying Alzheimer’s disease (AD) is important. Doing so allows us to identify biological pathways underlying AD, point towards novel drug targets and use the variants for individualised risk predictions in disease modifying or prevention trials. In the present work we report on the largest genome-wide association study (GWAS) for AD risk to date and show the combined utility of proven AD loci for precision medicine using polygenic risk scores (PRS).

METHODS

Three sets of summary statistics were included in our meta-GWAS of AD: an Spanish case-control study (GR@ACE/DEGESCO study, n = 12,386), the case-control study of International Genomics of Alzheimer project (IGAP, n = 82,771) and the UK Biobank (UKB) AD-by-proxy case-control study (n=314,278). Using these resources, we performed a fixed-effects inverse-variance-weighted meta-analysis. Detected loci were confirmed in a replication study of 19,089 AD cases and 39,101 controls from 16 European-ancestry cohorts not previously used. We constructed a weighted PRS based on the 39 AD variants. PRS were generated by multiplying the genotype dosage of each risk allele for each variant by its respective weight, and then summing across all variants. We first validated it for AD in independent data (assessing effects of sub-threshold signal, diagnostic certainty, age at onset and sex) and tested its effect on risk (odds for disease) and age at onset in the GR@ACE/DEGESCO study.

FINDINGS

Using our meta-GWAS approach and follow-up analysis, we identified novel genome-wide significant associations of six genetic variants with AD risk (rs72835061-CHRNE, rs2154481-APP, rs876461-PRKD3/NDUFAF7, rs3935877-PLCG2 and two missense variants: rs34173062/rs34674752 in SHARPIN gene) and confirmed a stop codon mutation in the IL34 gene increasing the risk of AD (IL34-Tyr213Ter), and two other variants in PLCG2 and HS3ST1 regions. This brings the total number of genetic variants associated with AD to 39 (excluding APOE). The PRS based on these variants was associated with AD in an independent clinical AD-case control dataset (OR=1.30, per 1-SD increase in the PRS, 95%CI 1.18-1.44, p = 1.1×10−7), a similar effect to that in the GR@ACE/DEGESCO (OR=1.27, 95%CI 1.23-1.32, p = 7.4×10−39). We then explored the combined effects of these 39 variants in a PRS for AD risk and age-at-onset stratification in GR@ACE/DEGESCO. Excluding APOE, we observed a gradual risk increase over the 2% tiles; when comparing the extremes, those with the 2% highest risk had a 2.98-fold (95% CI 2.12–4.18, p = 3.2×10−10) increased risk compared to those with the 2% lowest risk (p = 5.9×10−10). Using the PRS we identified APOE ε33 carriers with a similar risk as APOE ε4 heterozygotes carriers, as well as APOE ε4 heterozygote carriers with a similar risk as APOE ε4 homozygote. Considering age at onset; there was a 9-year difference between median onset of AD the lowest risk group and the highest risk group (82 vs 73 years; p = 1.6×10−6); a 4-year median onset difference (81 vs 77 years; p = 6.9×10−5) within APOE ε4 heterozygotes and a 5.5-year median onset difference (78.5 vs 73 years; p = 4.6×10−5) within APOE ε4 carriers.

INTERPRETATION

We identified six novel genetic variants associated with AD-risk, among which one common APP variant. A PRS of all genetic loci reported to date could be a robust tool to predict the risk and age at onset of AD, beyond APOE alone. These properties make PRS instrumental in selecting individuals at risk in order to apply preventative strategies and might have potential use in diagnostic work-up.