ARTICLE https://doi.org/10.1038/s41467-021-22491-8 OPEN Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores 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 1234567890():,; 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. A full list of authors and their affiliations appears at the end of the paper. NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 T hus far, multiple loci associated with Alzheimer’s disease data, by-proxy case-control data, and the data from the Genome (AD) have been described next to causal mutations in two Research at Fundació ACE (GR@ACE) study19. We confirm the subunits of γ-secretases, membrane-embedded aspartyl observed associations in a large independent replication study. complexes (PSEN1, PSEN2 genes), and the gene encoding one Then, we construct an update of the PRS and test whether the target protein of these proteases, the amyloid precursor protein effects of the PRS are influenced by diagnostic certainty, sex and gene (APP). The most prominent locus, APOE, was detected AAO groups. Lastly, we test whether the PRS could be used to almost 30 years ago using linkage techniques1. In addition, identify individuals at the highest odds of having AD and we genome-wide association studies (GWAS) of AD case-control compared AAO of the AD cases. This study describes the iden- datasets and by-proxy AD case-control studies have identified 30 tification of six variants associated with AD risk and provides an genomic loci that modify the risk of AD2–7. These signals account extended PRS tool to select individuals at high risk of AD. for ~31% of the genetic variance of AD, leaving most of the genetic risk as yet uncharacterized8. Further disentangling the genetic constellation of common genetic variations underlying Results AD can drive our biological insights of AD and can point toward Meta-GWAS of AD. We combined data from three AD GWASs: novel drug targets. the summary statistics calculated from the GR@ACE19 case- There are over 50 million people living with dementia and the control study (6331 AD cases and 6055 controls), the IGAP20 global cost of dementia is well above 1 trillion US$9. This means case-control study (up to 30,344 AD cases and 52,427 controls) there is a medical and economical urgency to efficiently test and the UKB AD-by-proxy case-control study21 (27,696 cases of interventions that are under development. Therefore, to increase maternal AD with 260,980 controls, and 14,338 cases of paternal power and reduce duration of trials, pre-symptomatic patients AD with 245,941 controls, Fig. 1, Supplementary Data 1). that are at high genetic risk of disease are increasingly Although we observed inflation in the resulting summary statis- developed10. However, only carriers of causal mutations (APP, tics (λ median = 1.08; see Supplementary Fig. 1d), it was not PSEN1, and PSEN2) and the APOE ɛ4 allele are considered high driven by an un-modeled population structure (LD score risk, while other common and rare genetic variants are ignored11. regression intercept = 1.036). The full details of the studies are Despite that, the combined effects of all currently known variants described in methods. After study-specific variant filtering and in a polygenic risk score (PRS) is associated with the conversion quality-control procedures, we performed a fixed effects inverse- of mild cognitive impairment to AD12,13, the neuropathological variance-weighted meta-analysis22 on the summary statistics of hallmarks of AD, age at onset (AAO) of disease14–17 and lifetime the three studies. Using this strategy, we identified a genome-wide risk of AD18. significant (GWS) association (p < 5 × 10−8) for 36 independent In this work we aim to comprehend and expand the knowledge genetic variants in 35 genomic regions (the APOE region contains of the genetic landscape underlying AD and provide additional signals for ɛ4 and ɛ2). As a sensitivity analysis, we removed the evidence that a PRS of variants can be a robust tool to select high AD-by-proxy study and compared the resulted effect estimates risk individuals with an earlier AAO. We first performed a meta- with and without this dataset. We found a high correlation GWAS integrating all currently published GWAS case-control between the effect estimates from the case-control and by-proxy Meta-GWAS analysis Polygenic Risk Score Discovery. Meta-analysis Case-control + AD-by-proxy Pathological dataset GR@ACEa IGAPb UKBc Ncases=332e + 676f N=12,386 N=82,771 N=314,278 Ncontrols=1,386 Global N= 409,435 participants Diagnostic Concomitant Sensitivity analysis Case-control AD status Effect of sex Age at Onset certainty brain pathologies GR@ACEa IGAPb N= 12,386 N=82,771 Effects of sub-threshold signal Follow-up. Analysis of genome-wide significant loci GR@ACEa Ncases=6,331 EADB PGC-ALZ AD and Ncontrols=3,546g N=33,753 N=17,537 GBCS 8 cohorts 3 cohorts N=3,981 Risk stratification GR@ACEd ADDN NxC N=637 Replication APOE stratification N=1,078 2 cohorts N=1,202 Age at Onset Global N= 58,190 (19,089 Cases and 39,101 Controls) 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.19), bStageI + StageII (Kunkle et al.20), cBy proxy AD: Meta-analysis of maternal and paternal history of dementia (Marioni et al.21), 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. 2 NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 ARTICLE a b f c d e 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. approaches for the significant loci (R2 = 0.994, p = 8.1 × 10−37; able to replicate two loci (ELK2AP and SPPL2A regions) that Supplementary Fig. 1e). Four genomic regions were not pre- showed suggestive association with AD (p < 1 × 10−7 in discovery). viously associated with AD (see Manhattan Plot, Fig. 2a). Next, we aimed at replicating the associated loci in 16 cohorts (19,087 AD cases and 39,101 controls in total), many of them Polygenic risk scores. In order to assess the robustness and collected and analyzed by the European Alzheimer’s Disease combined effect of the genetic landscape of AD (Fig. 3, Sup- Biobank (JPND-EADB) project. We tested all variants with plementary Data 4), we constructed a weighted PRS based on suggestive association (p < 10−5) located within a 200 kb region the 39 genetic variants (excluding APOE genotypes) that from the sentinel SNP. Overall, 384 variants were tested in the showed GWS evidence of association with AD (see Methods, replication datasets (Supplementary Data 2). Discovery and Fig. 4 and Supplementary Data 5). We tested if the association replication were combined, and we identified associations in six of the PRS with AD is independent of clinically important variants comprising five genomic loci annotated using FUMA23 factors that are considered in the selection of individuals for (Table 1, Fig. 2b–f, Supplementary Fig. 2 and Supplementary clinical trials. First, we showed that the association of the PRS Results). In APP, we identified a common (MAF = 0.46) intronic with clinically diagnosed AD cases is similar to the association variant associated with a reduced risk of AD (rs2154481, OR = 0.95 with pathologically confirmed AD (OR = 1.30 vs. 1.38, per 1-SD [0.94–0.96], p = 1.39 × 10−11, Fig. 2f). In SHARPIN (SHANK increase in the PRS). In this setting, adding variants below the Associated RH Domain Interactor) gene, we found two missense GWS threshold did not lead to a more significant association of mutations (rs34173062/p.Ser17Phe and rs34674752/p.Pro294Ser) the PRS with AD (Fig. 4a). Next, we tested whether the PRS was that are in linkage equilibrium (R2 = 1.3 × 10−6, D′ = 0.014, associated with AD in the presence of concomitant brain p = 0.96). Both missense variants increased AD risk (p.Ser17Phe, pathologies (besides AD). Among our autopsy-confirmed AD MAF = 0.085, OR = 1.14 [1.10–1.18], p = 9.6 × 10−13 and p. patients (n = 332), 84% had at least one concomitant pathology, Pro294Ser, MAF = 0.052, OR = 1.13 [1.09–1.18], p = 1.0 × 10−9, and the PRS was associated with AD in the presence of all tested Fig. 2b). A variant close to the genes PRKD3 and NDUFAF7 concomitant pathologies (Fig. 4b). Moreover, the patients often (rs876461, MAF = 0.143) emerged as the most significant variant in had more than one concomitant pathology (48.8%), but no the region after the combined analysis (OR = 1.07 [1.05–1.09], difference was observed in the effect estimate of the PRS when p = 1.3 × 10−9, Fig. 2c). In the 3’-UTR region of CHRNE more than one pathology was present (Fig. 4b). Last, we (Cholinergic Receptor Nicotinic Epsilon Subunit), rs72835061 investigated the effect of sex and AAO (Fig. 4c). Our analysis (MAF = 0.085) was associated with a 1.09-fold increased risk of revealed that the effect of the PRS was the same in both sexes AD (95% CI [1.06–1.11], p = 1.5 × 10−10, Fig. 2e). Our analysis also (Fig. 4c) and was consistent with both early-onset (onset before strengthened the evidence of association with AD for three 65 years; OR = 1.58, 95% CI [1.22–2.05], p = 5.8 × 10−4) as well additional genomic loci including an association with a variant in as with late-onset AD (onset later than 85 years; OR = 1.29, 95% PLCG2 (rs3935877, MAF = 0.13, OR = 0.92 [0.90–0.95], p = 6.9 × CI [1.10–1.51], p = 1.5 × 10−3). 10−9, Fig. 2d), and confirmed another common variant in PLCG2, a PRSs has the potential to early identify subjects at risk of stop gain mutation in IL-34 and a variant near HS3ST1 (Table 1, complex diseases24. To identify people at the highest genetic Supplementary Fig. 3 and Supplementary Data 2, 3). We were not risk of AD based on the PRS, we used the validated 39-variants NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications 3 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 1.51 × 10−10 3.91 × 10−10 9.16 × 10−12 6.81 × 10−12 9.62 × 10−13 PRS in the large GR@ACE dataset. The PRS was associated with a 1.39 × 10−11 1.34 × 10−9 1.00 × 10−9 6.85 × 10−9 9.04 × 10−7 1.08 × 10−7 1.27-fold (95% CI [1.23–1.32]) increased risk for every standard deviation increase in the PRS (p = 7.3 × 10−39) and with a gradual risk increase when we stratified the dataset into 2% P percentiles of the PRS (Fig. 5a, Supplementary Data 6). Next, we stratified the dataset in APOE genotype risk groups. The PRS [0.90–0.95] [0.94–0.96] 0.95 [0.93–0.96] 0.94 [0.92–0.95] 0.94 [0.92–0.97] [1.05–1.09] 1.05 [1.03–1.08] [1.09–1.18] [1.10–1.18] [1.06–1.11] 1.08 [1.06–1.11] percentiles were associated with AD within the APOE genotype OR [CI 95%] groups (Fig. 5b, Supplementary Data 7). Finally, we compared the risk extremes and found a 16.2-fold (95% CI [8.84–29.5], Overall p = 1.5 × 10−19) increased risk for the highest-PRS group (APOE 1.09 1.07 1.13 1.14 0.92 0.95 ɛ4ɛ4) compared with the lowest-PRS group (APOE ɛ2ɛ2/ɛ2ɛ3; Supplementary Data 8). When we compared the median AAO in AD patients in these extreme risk groups we found a 9-year 3.07 × 10−4 1.65 × 10−5 1.96 × 10−2 3.23 × 10−5 7.35 × 10−3 7.83 × 10−3 3.31 × 10−3 4.54 × 10−3 4.59 × 10−3 difference in the median age (pWilcoxon = 1.7 × 10−6) (Fig. 5c). Results obtained with a fixed effects inverse-variance-weighted meta-analysis on the discovery and follow-up stages. Freq A1 is from GR@ACE discovery dataset. P value for significance <5 × 10−8. Effect allele: A1. Lastly, we studied the effects on AAO of the PRS in the APOE 0.0412 0.3501 genotype groups. The PRS differentiated AAO only within APOE ɛ4 carriers. In APOE ɛ4 heterozygotes the PRS determined a 4- P year difference in median AAO and in APOE ɛ4 homozygotes (pWilcoxon = 6.9 × 10−5), where the PRS determined a median Follow-up datasets 0.93 [0.88–0.98] 0.92 [0.88–0.96] [0.85–0.99] [0.93–0.99] 1.02 [0.97–1.07] AAO difference of 5.5 years (pWilcoxon = 4.6 × 10−5). For the [1.04–1.13] 1.09 [1.03–1.16] [1.02–1.17] [1.02–1.12] 1.16 [1.01–1.33] [1.10–1.31] OR [CI 95%] selection of high-risk individuals, it is important to note that we found no difference in the odds and AAO for AD for APOE ɛ4 heterozygotes with the highest PRS compared to APOE ɛ4 1.20 1.07 0.96 1.08 1.09 0.92 homozygotes with the lowest PRS. The Cox regression also showed an impact of APOE on AAO, mainly on APOE ε4ε4 (significant APOE-PRS interaction (p = 0.021), Fig. 5d, Supple- 9.26 × 10−10 5.37 × 10−10 1.33 × 10−11 4.02 × 10−6 3.92 × 10−9 2.28 × 10−8 1.48 × 10−8 9.80 × 10−8 6.86 × 10−8 9.14 × 10−7 1.12 × 10−7 mentary Data 9). Discovery meta-analysis P Discussion This work adds on the ongoing global effort to identify genetic [0.90–0.95] 0.94 [0.92–0.96] 0.94 [0.92–0.96] [0.93–0.96] 0.95 [0.93–0.97] variants associated with AD (Fig. 3). In the present work, we [1.04–1.09] 1.06 [1.04–1.08] [1.06–1.16] [1.06–1.12] 1.08 [1.05–1.11] [1.11–1.21] reported on the largest GWAS for AD risk to date, comprising OR [CI 95%] genetic information of 467,623 individuals of European ancestry. We identified six variants that were not previously associated with the risk of AD and constructed a robust PRS for AD demon- 1.07 1.16 1.11 0.92 1.09 0.95 strating its potential value for selecting subjects at risk of AD, especially within APOE ɛ4 carriers. This PRS was based on Freq A1 European ancestries and may or may not generalize to other 0.407 0.085 0.085 0.684 0.802 0.868 0.052 0.750 0.483 0.143 ancestries. Validation in other populations will be required. We 0.111 also acknowledge that controls included in GR@ACE are younger Previously reported genome-wide significant hits replicating in the follow-up than cases and some of the controls might still develop AD later A2 in life. This fact does not invalidate the analysis although reported G G G G G C C T T T T Variants showing novel genome-wide significant association with AD estimates must be considered conservative. The differences in risk Table 1 Association for the AD loci selected for follow-up. and AAO determined by the PRS of AD are relevant for design A1 A A A A A A C C C C C clinical trials that over-represent APOE ε4 carriers, as APOE ε4 heterozygous with highest-PRS values have a similar risk and 70694000 145158607 145154222 AAO to APOE ɛ4 homozygotes (Fig. 5b). These represents ~1% 106195719 27473875 81900853 51002342 81773209 37515958 4805437 11027619 of our control population, which is the same percentage as all APOE ε4 homozygotes. A trial that aims to include APOE ɛ4 BP homozygotes, could consider widening the selection criteria and in this way hasten the enrollment process. Also, our PRS could rs34674752 rs76523702 rs34173062 rs72835061 rs12444183 aid at the interpretation of the results of clinical trials, as it rs4985556 rs3935877 rs4351014 rs2154481 rs7153315 rs876461 determines a relevant proportion of the AAO, which could either Suggestive signals (not replicating) mimic or obscure a treatment effect. SNP The most interesting finding from our GWAS is the discovery of a common protective (MAF (C-allele) = 0.483) intronic variant in the APP gene. Our results directly support APP production or PRKD3/NDUFAF7 processing as a causal pathway not only in familial AD but in Closest gene common sporadic AD. The SNP is in a DNase hypersensitive area SHARPIN SHARPIN of 295 bp (chr21:27473781-27474075) possibly involved in the ELK2AP SPPL2A HS3ST1 CHRNE PLCG2 PLCG2 transcriptional regulation of the APP gene. rs2154481 is an eQTL IL34 APP for the APP mRNA and an antisense transcript of the APP gene named AP001439.2 in public eQTL databases25 (Supplementary Chr Fig. 4). Functional evidence supports a modified APP 14 16 16 16 17 21 15 4 8 8 2 transcription26 as an LD block of 13 SNPs within the APP locus 4 NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 ARTICLE 200000 Family Candidate−gene GWAS studies Marioni et al. Current study Study size studies studies Nicolas et al. 100000 Benitez et al. Kunkle et al. Lambert et al. Hollingworth et al. Sims et al. Jansen et al. Harold et al. Jun et al. Broce et al. 20000 Rogaeva et al. Lambert et al. Desikan et al. Strittmatter et al. Jonsson et al. Seshadri et al. Goate et al. Chartier−Harlin et al. Bertram et al. Jonsson et al. Shellenberg et al. 10 Levy−Lahad et al. OR<1.1 50 APP OR=1.2 ACE SPI1 OR=2 PLCG2 40 ECHDC3 PTK2B Variant frequency (%) MS4A4A CLU BIN1 OR>3 PICALM HS3ST1 CD2AP OR>0.95 30 CD33 PILRA TREML2 SLC2A4 OR=0.75 ABCA7 INPP5D ADAM10 MAPT OR=0.5 20 IQCK EPHA1 PRKD3 APOE4 CR1 APH1B PLCG2 Gene Culprit gene found CASS4 SCIMP Gene Culprit gene not found 10 HLA−DRB1 IL34 MINK1 SHARPIN S17F APOE2 SORL1 FERMT2 PLCG2 − P522R SHARPIN P294S ABCA7 TREM2 −R62H 1 TREM2 −R47H ABI3 APP SORL1 APP − A673T PSEN1 PSEN2 0 1990s y 08 09 10 11 12 13 14 15 16 17 18 19 ud 20 20 20 20 20 20 20 20 20 20 20 20 st nt re ur C Timeline 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.3, Kunkle et al.20, Jun et al.43, Sims et al.7, Jansen et al.38 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. (including rs2154481) increased the TFCP2 transcription factor roles. We add to the growing body of evidence that the polygenic avidity to its binding site and increased the enhancer activity of scores of all genetic loci to date, in combination with APOE this specific intronic region26. Based on this evidence, we can genotypes, are robust tools that are associated with AD and its postulate that a life-long slightly higher APP gene expression AAO. These properties make PRS promising in selecting indivi- protects the brain from AD insults. Still, this seems counter- duals at risk to apply preventative therapeutic strategies. intuitive as duplications of the gene lead to early-onset AD27. A U-shaped effect, or hormesis effect of APP might help explain our Methods observations and it might also fit the accelerated cognitive dete- Data. Participants in this study were obtained from multiple sources, including raw rioration observed in AD patients treated with beta-secretase data from case-control samples collected by GR@ACE/DEGESCO, summary sta- inhibitors28,29 as these reduce beta-amyloid in their brain. An tistics data from the case-control samples in the IGAP and the summary statistics alternative hypothesis is that mechanisms underlying the variant of AD-by-proxy phenotype from the UK Biobank. An additional case-control samples from 16 independent cohorts (19,087 AD cases and 39,101 controls) was are related to the overexpression of protective fragments of the used for replication, largely collected and analyzed by the European Alzheimer’s APP protein30. Disentangling the molecular mechanism of our Disease Biobank (JPND-EADB) project. Full descriptions of the samples and their finding will help refine and steer the amyloid hypothesis. respective phenotyping and genotyping procedures are provided in the Supple- Additionally, other three variants identified are altering protein mentary Methods. sequence or affecting regulatory motifs. Two independent mis- GR@ACE. The GR@ACE study19 recruited AD patients from Fundació ACE, sense mutations in SHARPIN increased the AD risk. SHARPIN Institut Català de Neurociències Aplicades (Catalonia, Spain), and control indivi- was previously proposed as an AD candidate gene31,32, and duals from three centers: Fundació ACE (Barcelona, Spain), Valme University functional analysis of a rare missense variant (NM_030974.3:p. Hospital (Seville, Spain), and the Spanish National DNA Bank–Carlos III (Uni- Gly186Arg) resulted in the aberrant cellular localization of the versity of Salamanca, Spain) (http://www.bancoadn.org). Additional cases and controls were obtained from dementia cohorts included in the Dementia Genetics variant protein and attenuated the activation of NF-κB, a central Spanish Consortium (DEGESCO)33. At all sites, AD diagnosis was established by a mediator of inflammatory and immune responses. Functional multidisciplinary working group—including neurologists, neuropsychologists, and analysis of the two identified missense variants will show if the social workers—according to the DSM-IV criteria for dementia and the National effect on immune reaction in AD is similar. The variant located in Institute on Aging and Alzheimer’s Association’s (NIA–AA) 2011 guidelines for the CHRNE which encodes a subunit of the cholinergic receptor diagnosing AD. In our study, we considered as AD cases any individuals with dementia diagnosed with probable or possible AD at any point in their clinical (AChR) is a strong modulator of CHRNE expression. The same course. For further details on the contribution of the sites, see Supplementary allele that increases AD risk increases the expression in the brain Data 10. Written informed consent was obtained from all the participants. The and other tissues according to GTEx (p = 2.1 × 10−13) (Supple- ethics and scientific committees have approved this research protocol (Acta 25/ mentary Fig. 5). The detection of a potential hypermorph allele 2016, Ethics Committee H., Clinic I Provincial, Barcelona, Spain). Genotyping, quality control, and imputation. DNA was extracted from linked to AD risk and affecting cholinergic function could rein- peripheral blood according to standard procedures using the Chemagic system troduce this neurotransmitter pathway into the search for pre- (Perkin Elmer). Samples reaching DNA concentrations of >10 ng/μl and presenting ventative strategies. Further functional studies are needed to high integrity were included for genotyping. Cases and controls were randomized consolidate this hypothesis. across sample plates to avoid batch effects. Genotyping was conducted using the Axiom 815K Spanish biobank array Altogether, we described six additional loci associated with (Thermo Fisher) at the Spanish National Center for Genotyping (CeGEN, Santiago sporadic AD. These signals reinforce that AD is a complex disease de Compostela, Spain). The genotyping array not only is an adaptation of the in which amyloid processing and immune response play key Axiom biobank genotyping array but also contains rare population-specific NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications 5 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 a b c 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 (ORmales = 1.33, [1.13–1.56], p = 5.8 × 10−4 vs. ORfemales = 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. variations observed in the Spanish population. The DNA samples were genotyped was determined based on the resolution of AT and GC channels in a group of non- according to the manufacturer’s instructions (Axiom™ 2.0 Assay Manual polymorphic SNPs (resolution > 0.82). Samples with a call rate greater than 97% Workflow). The Axiom 2.0 assay interrogates biallelic SNPs and simple indels in a and plates with an average call rate above 98.5% were included for final SNP single-assay workflow. Starting with 200 ng of genomic DNA, the samples were calling. The samples were jointly called. Markers passing all the QC tests were used processed through a manual target preparation protocol, followed by automated in downstream analysis (NSNPs = 729,868; 95.4%) using the SNPolisher R package processing of the array plates in the GeneTitan Multi-Channel (MC) instrument. (Thermo Fisher). To assess the sample genotyping concordance, we intentionally Target preparation involved DNA amplification, fragmentation, purification, and resampled 200 samples and determined a concordance rate of 99.5%. resuspension of the target in a hybridization cocktail. The hyb-ready targets were We also conducted previously described standard QC prior to imputation19. In then transferred to the GeneTitan MC instrument for automated, hands-free brief, individual QC includes genotype call rates >97%, sex checks, and no excess processing, including hybridization, staining, washing, and imaging. The CEL files heterozygosity; we removed population outliers as well (European cluster of 1000 were generated using the GeneTitan MC instrument. Quality control (QC) was Genomes). We included variants with a call rate of >95%, with a minor allele performed for samples and plates using the Affymetrix power tool (APT) frequency (MAF) of >0.01, in Hardy–Weinberg equilibrium (p < 1 × 10−4 in 1.15.0 software following the Axiom data analysis workflow. The sample quality controls) and without differential missingness between cases and controls 6 NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 ARTICLE a b c d 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, pWilcoxon = 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 (pWilcoxon = 6.9 × 10−5, 81 years compared with 77 years) and 5.5 years difference (pWilcoxon = 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). (Supplementary Data 11, Supplementary Fig. 1). Imputation was carried out using (2006–2010) (http://www.ukbiobank.ac.uk)36. Several groups have demonstrated the Haplotype reference consortium34 (HRC, full panel) and the 1000 Genomes the utility of self-report of parental history of AD for case ascertainment in GWAS reference panel35 (for indels only) on the Michigan Imputation Server (https:// (proxy–AD approach)21,37,38. For this study, we used the published summary imputationserver.sph.umich.edu). Rare variants (MAF < 0.001) and variants with statistics of Marioni et al.21. They included, after stringent QC, 314,278 unrelated low imputation quality (R2 < 0.30) were excluded. Logistic regression models, individuals for whom AD information was available on at least one parent in the adjusted for the first four ancestry principal components19, were fitted using Plink UK Biobank (https://datashare.is.ed.ac.uk/handle/10283/3364). In brief, the 27,696 (v2.00a). Population-based controls were used; therefore, age was not included as a participants whose mothers had dementia (maternal cases) were compared with covariate. Age and gender statistically behave like phenotype proxies (for AD status the 260,980 participants whose mothers did not have dementia. Likewise, the in this case). Therefore, adjusting for co-variation with age and gender could result 14,338 participants whose fathers had dementia (paternal cases) were compared in an over-adjustment of GWAS results. After QC steps, we included 6,331 AD with the 245,941 participants whose fathers did not have dementia21. The phe- cases and 6,055 control individuals and tested 14,542,816 genetic variants for notype of the parents is independent, and therefore, the estimates could be meta- association with AD. analyzed. After analysis, the effect estimates were made comparable to a case- control setting. Further information on the transformation of the effect sizes can be IGAP summary statistics. The GWAS summary results from the IGAP were found elsewhere21,39. The data available comprises summary statistics of 7,794,553 downloaded from the National Institute on Aging Genetics of Alzheimer’s Disease SNPs imputed to the HRC reference panel (full panel). Data Storage Site (NIAGADS, https://www.niagads.org/)20. Details on data gen- eration and analyses by the IGAP have been previously described20. In brief, the Meta-GWAS of AD. After study-specific variant filtering and quality-control IGAP is a large study based upon genome-wide association using individuals of procedures, we performed a fixed effects inverse-variance–weighted meta- European ancestry. Stage 1 of the IGAP comprises 21,982 AD cases and 41,944 analysis22 on the discovery and follow-up stages (Supplementary Data 1 and cognitively normal controls from four consortia: the Alzheimer Disease Genetics Supplementary Data 12). To determine the lead SNPs (those with the strongest Consortium (ADGC), the European Alzheimer’s Disease Initiative (EADI), the association per genomic region), we performed clumping on SNPs with a GWS p Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) value (p < 5 × 10−8) (Plink v1.90, maximal linkage disequilibrium (LD) with R2 < Consortium, and the Genetic and Environmental Risk in AD/Defining Genetic, 0.001 and physical distance 250 Kb). In the APOE region, we only considered the Polygenic, and Environmental Risk for Alzheimer’s Disease (GERAD/PERADES) APOE ɛ4 (rs429358) and APOE ɛ2 (rs7412) SNPs40. LD information was calculated Consortium. Summary statistics are available for 11,480,632 variants, both geno- using the GR@ACE imputed genotypes as a reference. Polygenicity and con- typed and imputed (1000 Genomes phase 1, v3). In Stage 2, 11,632 SNPs were founding biases, such as cryptic relatedness and population stratification, can yield genotyped in an independent set of 8362 AD cases and 10,483 controls. an inflated distribution of test statistics in GWAS. To distinguish between inflation from a true polygenic signal and bias we quantified the contribution of each by UK Biobank summary statistics. UK Biobank data—including health, cognitive, and examining the relationship between test statistics and linkage disequilibrium (LD) genetic data—was collected on over 500000 individuals aged 37–73 years from using the LD Score regression intercept (LDSC software41). Chromosomal regions across Great Britain (England, Wales, and Scotland) at the study baseline associated with AD in previous studies were excluded from follow-up (Lambert NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications 7 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 et al.3, Kunkle et al.42, and Jansen et al.38). We tested all variants with suggestive Reporting summary. Further information on research design is available in the Nature association (p < 10−5) located in proximity (200 kb) of genomic regions selected for Research Reporting Summary linked to this article. follow-up to allow for the potential refinement of the top associated variant. Conditional analyses were performed in regions where multiple variants were associated with AD using logistic regression models, adjusting for the genetic Data availability variants in the region (Supplementary Data 13, 14). The discovery summary statistics of this study are publicly available in Fundació ACE Regional plots were generated with a mixture of homemade Python (v2.7) and server [https://fundacioace-my.sharepoint.com/:u:/g/personal/iderojas_fundacioace_org/ R (v3.6.0) scripts. Briefly, given an input variant, we calculated the LD between the EaTwlPg9cRJHn7Kos4h39OUBaxajsjJHL_C110fC89bc8w?e=ZdcEUy]. input variant and all the surrounding variants within a window of length defined by the user. The LD was calculated in the 1000 Genomes samples of European Received: 17 July 2020; Accepted: 17 March 2021; ancestry. We used gene positions from RefSeq (release 93); in the case of multiple gene models for a given gene, we reported the model with the largest number of exons. We used recombination rates from HapMap II and chromatin states from ENCODE/Broad (15 states were grouped to highlight the predicted functional elements). As a reference genome, we used GRCh37. Quantile–quantile plots, Manhattan plots, and the exploration of genomic inflation factors were performed using the R package qqman. References 1. Pericak-Vance, M. A. et al. Linkage studies in familial Alzheimer disease: evidence for chromosome 19 linkage. Am. J. Hum. Genet. 48, 1034–1050 (1991). Polygenic risk scores. We calculated a weighted individual PRS based on the 39 2. Seshadri, S. et al. Genome-wide analysis of genetic loci associated with genetic variants that showed GWS evidence of association with AD in the present Alzheimer disease. JAMA J. Am. Med. Assoc. 303, 1832–1840 (2010). study, excluding APOE to check the impact of PRS modulating APOE risk (Table 1 3. Lambert, J. C. et al. Meta-analysis of 74,046 individuals identifies 11 new and Supplementary Data 3). The selected variants were directly genotyped or susceptibility loci for Alzheimer’s disease. Nat. Genet. 45, 1452–1458 (2013). imputed with high quality (median imputation score R² = 0.93). The PRSs were 4. Jonsson, T. et al. Variant of TREM2 associated with the risk of Alzheimer’s generated by multiplying the genotype dosage of each risk allele for each variant by disease. N. Engl. J. Med. 368, 107–116 (2013). its respective weight and then summing across all variants. We weighted this by the effect size from previous IGAP studies [Kunkle et al.42 (36 variants), Sims et al.7 (2 5. Guerreiro, R. et al. TREM2 variants in Alzheimer’s disease. N. Engl. J. Med. variants), Jun et al.43 (MAPT locus), Supplementary Data 5]. The generated PRS 368, 117–127 (2013). was validated using logistic regression adjusted by four principal components in a 6. Jonsson, T. et al. A mutation in APP protects against Alzheimer’s disease and sample of 676 AD cases diagnosed based on clinical criteria and 332 pathologically age-related cognitive decline. Nature 488, 96–99 (2012). confirmed AD cases from the European Alzheimer’s Disease Biobank–Fundació 7. Sims, R. et al. Rare coding variants in PLCG2, ABI3, and TREM2 implicate ACE/Barcelona Brain Bank dataset (EADB–F.ACE/BBB, Supplementary Infor- microglial-mediated innate immunity in Alzheimer’s disease. Nat. Genet. 49, mation). This dataset was not used in prior genetic studies. In this dataset, all 1373–1384 (2017). pathologically confirmed cases were scored for the presence or absence of con- 8. Ridge, P. G. et al. 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Clinical trials of new drugs for used strict settings for clumping (R2 = 0.001 and window = 1 MB) and increasing p Alzheimer disease. J. Biomed. Sci. 27, 18 (2020). value thresholds (>1 × 10−7, >1 × 10−6, >1 × 10−5, >1 × 10−4, >1 × 10−3, and >1 × 12. Rodríguez-Rodríguez, E. et al. Genetic risk score predicting accelerated 10−2). We tested the association of the results with clinically diagnosed and progression from mild cognitive impairment to Alzheimer’s disease. J. Neural pathologically confirmed AD patients. To evaluate the effect of diagnostic certainty, Transm. 120, 807–812 (2013). we tested whether the PRS was different between the two patient groups. For the 13. Adams, H. H. H. et al. Genetic risk of neurodegenerative diseases is associated PRS with 39 GWS variants, we tested whether the PRS had sex-specific effects, with mild cognitive impairment and conversion to dementia. 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Wide Association Studies23 (FUMA, v1.3.4c) to interpret SNP-trait associations 22. Willer, C. J., Li, Y. & Abecasis, G. R. METAL: Fast and efficient meta-analysis (see Supplementary Methods and Supplementary Data 15–18). FUMA is an online of genomewide association scans. Bioinformatics https://doi.org/10.1093/ platform that annotates GWAS findings and prioritizes the most likely causal SNPs bioinformatics/btq340 (2010) . and genes using information from 18 biological data repositories and tools. As 23. Watanabe, K., Taskesen, E., van Bochoven, A. & Posthuma, D. Functional input, we used the summary statistics of our meta-GWAS. Gene prioritization is mapping and annotation of genetic associations with FUMA. Nat. Commun. based on a combination of positional mapping, expression quantitative trait loci https://doi.org/10.1038/s41467-017-01261-5 (2017). (eQTL) mapping, and chromatin interaction mapping. Functional annotation was 24. Khera, A. V. et al. Genome-wide Polygenic Scores for Common Diseases performed by applying a methodology similar to that described by Jansen et al.38. Identify Individuals With Risk Equivalent to Monogenic Mutations. Nat. We referred to the original publication for details on the methods and repositories Genet. 50, 1219–1224 (2018). of FUMA23. 8 NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 ARTICLE 25. Lonsdale, J. et al. The genotype-tissue expression (GTEx) project. Nat. Genet. 733051061). Longitudinal Aging Study Amsterdam (LASA) is largely supported by a 45, 580–585 (2013). grant from the Netherlands Ministry of Health, Welfare and Sports, Directorate of Long- 26. Myrum, C., Nikolaienko, O., Bramham, C. R., Haavik, J. & Zayats, T. Term Care. The authors are grateful to all LASA participants, the fieldwork team and all Implication of the APP gene in intellectual abilities. J. Alzheimer’s Dis 59, researchers for their ongoing commitment to the study. This work was supported by a 723–735 (2017). grant (European Alzheimer DNA BioBank, EADB) from the EU Joint Program—Neu- 27. Cenini, G. et al. Wild type but not mutant APP is involved in protective rodegenerative Disease Research (JPND) and also funded by Inserm, Institut Pasteur de adaptive responses against oxidants. Amino Acids 39, 271–283 (2010). Lille, the Lille Métropole Communauté Urbaine, the French government’s LABEX 28. Egan, M. F. et al. Randomized trial of verubecestat for mild-to-moderate DISTALZ program (development of innovative strategies for a transdisciplinary Alzheimer’s disease. N. Engl. J. Med. 378, 1691–1703 (2018). approach to AD). Genotyping of the German case-control samples was performed in the 29. Panza, F., Lozupone, M. & Watling, M. & Imbimbo, B. P. Do BACE inhibitor context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND failures in Alzheimer patients challenge the amyloid hypothesis of the disease? (German Federal Ministry of Education and Research, BMBF: 01ED1619A). Full Expert Rev. Neurother. 19, 599–602 (2019). acknowledgments for the studies that contributed data can be found in the Supple- 30. Hefter, D. & Draguhn, A. APP as a protective factor in acute neuronal insults. mentary Note. We thank the numerous participants, researchers, and staff from many Front. Mol. Neurosci. 10, 22 (2017). studies who collected and contributed to the data. We thank the International Genomics 31. Lancour, D. et al. One for all and all for One: Improving replication of genetic of Alzheimer’s Project (IGAP) for providing summary results data for these analyses. The studies through network diffusion. PLoS Genet 14, e1007306 (2018). investigators within IGAP contributed to the design and implementation of IGAP and/or 32. Asanomi, Y. et al. A rare functional variant of SHARPIN attenuates the provided data but did not participate in analysis or writing of this report. IGAP was made inflammatory response and associates with increased risk of late-onset possible by the generous participation of the control subjects, the patients, and their Alzheimer’s disease. Mol. Med. 25, 20 (2019). families. The i–Select chips was funded by the French National Foundation on AD and 33. Ruiz, A. et al. Assessing the role of the TREM2 p.R47H variant as a risk factor related disorders. EADI was supported by the LABEX (laboratory of excellence program for Alzheimer’s disease and frontotemporal dementia. Neurobiol. Aging 35, investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université 444.e1–444.e4 (2014). de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical 34. McCarthy, S. et al. A reference panel of 64,976 haplotypes for genotype Research Council (Grant n° 503480), Alzheimer’s Research UK (Grant n° 503176), the imputation. Nat. Genet. 48, 1279–1283 (2016). Wellcome Trust (Grant n° 082604/2/07/Z) and German Federal Ministry of Education 35. 1000 Genomes Project Consortium. et al. A global reference for human and Research (BMBF): Competence Network Dementia (CND) grant n° 01GI0102, genetic variation. Nature 526, 68–74 (2015). 01GI0711, 01GI0420. CHARGE was partly supported by the NIA/NHLBI grants 36. Sudlow, C. et al. UK Biobank: an open access resource for identifying the AG049505, AG058589, HL105756 and AGES contract N01–AG–12100, the Icelandic causes of a wide range of complex diseases of middle and old Age. PLOS Med. Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was 12, e1001779 (2015). supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and 37. Liu, J. Z., Erlich, Y. & Pickrell, J. K. Case-control association mapping by the Alzheimer’s Association grant ADGC–10–196728. This research has been conducted proxy using family history of disease. Nat. Genet. 49, 325–331 (2017). using the UK Biobank public resource obtained through the University of Edinburg Data 38. Jansen, I. E. et al. Genome-wide meta-analysis identifies new loci and Share (https://datashare.is.ed.ac.uk/handle/10283/3364). functional pathways influencing Alzheimer’s disease risk. Nat. Genet. 51, 404–413 (2019). 39. Lloyd-Jones, L. R., Robinson, M. R., Yang, J. & Visscher, P. M. Transformation Author contributions of summary statistics from linear mixed model association on all-or-none A.Ru and S.v.d.L. designed and conceptualized the study, interpreted the data and drafted traits to odds ratio. Genetics 208, 1397–1408 (2018). the paper. I.d.R. contributed to data acquisition, the analysis, interpreted the data, and 40. Jun, G. et al. Comprehensive search for Alzheimer disease susceptibility loci in co-wrote the paper. S.M.G. and N.T. contributed to the analysis and interpreted the data. the APOE region. Arch. Neurol. 69, 1270–1279 (2012). S.J.v.d.L. and I.d.R. performed polygenic score analyses. L.C.C. and J.C. conducted the 41. Bulik-Sullivan, B. et al. LD score regression distinguishes confounding from functional analysis of APP. H.Ho, W.v.d.F., S.J.v.d.L., and A.Ru supervised the study. All polygenicity in genome-wide association studies. Nat. Genet. https://doi.org/ authors critically revised the paper for important intellectual content and approved the 10.1038/ng.3211 (2015). final paper. GR@ACE/DEGESCO: Study design or conception: M.Me, J.C., and A.Ru. 42. Kunkle, B. W. et al. Genetic meta-analysis of diagnosed Alzheimer’s disease Data generation: L.M., L.C.C., A.G.P., M.E.S., S.M.G., I.d.R., I.Q., and A.C. Sample identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. contribution: M.Bo, J.M.G.A., M.Me, M.Ma, M.C., T.S., S.G.M., G.G.R., A.L.M., J.M., L. Nat. Genet. 51, 414–430 (2019). M.R., G.P.R., M.M.G., C.M.R., I.R.A., V.A.l., C.L., E.R.R., P.S.J., D.A.l., P.P., M.D.F., I.A.l., 43. Jun, G. et al. A novel Alzheimer disease locus located near the gene encoding J.P.T., A.C., L.Ta, A.M.M., M.J.B., A.F.G., I.Q., I.H., L.M., P.G.G., E.A.M., S.V., O.S.G., A. tau protein. Mol. Psychiatry 21, 108–117 (2016). Bena, A.P.C., A.E., A.Sa, C.Ab, G.O., M.R.R., M.A.l., N.R., S.G., A.O., A.Rab, A.Bel, F.Mo, M.Z., A.C.G., J.A.P., M.F.F., E.F.M., D.B.R., M.B.S.A., P.M., R.H.V., A.A.P., A.A., L.M.P., R.S.V., E.Ge, A.L., R.B., J.F., J.L.R., S.Men, M.Ba, I.d.R., and S.M.G. Analysis: S.M.G. and Acknowledgements I.d.R. Study supervision/management: A.C., L.Ta, M.Bo, M.Me, J.C., and A.Ru. IGAP. We would like to thank patients and controls who participated in this project. The Critical revision: A.C.N., B.W.K., L.A.F., J.L.H., L.S.W., M.A.P.V., R.May, M.A.I., J.C.B., present work has been performed as part of the doctoral program of I. de Rojas at the A.L.D.S., C.L.S., E.B., M.F., Q.Y., X.J., R.S., C.H., K.M., S.Mea, V.E.P., A.Meg, P.A.H., R. Universitat de Barcelona (Barcelona, Spain) supported by national grant from the Mar, P.A., G.Sc, J.Will, and S.Se. EADB: Sample contribution. N.T., I.E.J., N.St, K.A.M., Instituto de Salud Carlos III FI20/00215. The Genome Research @ Fundació ACE project C.D., G.N., G.C., G.Sp, K.S., M.I., M.K., R.F.S., J.C.L., A.Ra, D.G., J.S.V., D.R., E.Gr, H.Ha, (GR@ACE) is supported by Grifols SA, Fundación bancaria “La Caixa”, Fundació ACE, I.G., J.K., L.Fa, L.Fr, A.M.H., J.V., L.H., G.H., N.Sca, M.H.K., M.Y., H.Ho, W.M.v.d..F, M. and CIBERNED. A.R. and M.B. receive support from the European Union/EFPIA H.u.l., N.M.v.S., A.T.H., B.G.N., C.V.B., E.S., R.V., S.E., T.N., F.K., J.V.D., V.G., A.U., A. Innovative Medicines Initiative Joint undertaking ADAPTED and MOPEAD projects Benu, A.K.S., B.B., C.Mas, C.F., E.C., F.Ma, G.B., I.Ap, J.Q.T., L.Ki, L.K.l., L.P., L.Tr, L.B., (grant numbers 115975 and 115985, respectively). M.B. and A.R. are also supported by M.L., M.Ar, R.G., S.F., F.J., J.D.S., O.G., T.G., M.J.H., T.P., K.Bu, M.E.si, S.R.H., E.Dur, A. national grants PI13/02434, PI16/01861, PI17/01474, PI19/01240 and PI19/01301. Ru, I.H., S.M.G., I.d.R., Y.A.L..P, A.d.M., C.C.l., J.P., S.J.v.d.L., C.G., N.B., O.H., P.B., A. Acción Estratégica en Salud is integrated into the Spanish National R + D + I Plan and H., T.K., M.E.w., O.A.S., R.N.K., J.Wilf, P.F., P.R., P.Sc, P.Sa, N.Sch, D.W., E.R., G.R., H. funded by ISCIII (Instituto de Salud Carlos III)—Subdirección General de Evaluación S., I.R., A.Sc, A.Sp, A.Sq, C.Cha, C.Chi, C.P., A.P., B.A., B.N., C.M.F., D.S., E.Da, E.düz, E. and the Fondo Europeo de Desarrollo Regional (FEDER—“Una manera de hacer F., F.T., F.P., F.S.G., G.Gi, G.Gra, G.P., H.B., J.H., J.L., M.C.D., M.T., M.T.H., M.Schm, M. Europa”). Some control samples and data from patients included in this study were W., M.S., O.Q., O.L., P.C., P.D., R.C., S.So, S.He, S.A., S.B., S.C., T.L., V.B., V.D., P.G.K., provided in part by the National DNA Bank Carlos III (www.bancoadn.org, University of M.M.N., M.C.D.N., O.P., W.M., A.W.L., I.Ap, C.B.F., A.A.L.K., G.B., M.Sca, M.Sp, M.V., Salamanca, Spain) and Hospital Universitario Virgen de Valme (Sevilla, Spain); they M.Hi, K.F., L.W., M.D., P.H., and A.Ra. Analysis: N.J.A., R.M.T., V.An, N.T., I.E.J., N.St, were processed following standard operating procedures with the appropriate approval of S.J.v.d.L., I.d.R., S.M.G., B.G.B., and C.B. Studies supervision/management: S.H.H., K.A. the Ethical and Scientific Committee. Amsterdam dementia Cohort (ADC): Research of M., C.D., G.N., G.C., G.S., K.S., M.I., M.K., R.F.S., D.G., J.S.V., D.R., E.Gr, H.Ha, I.G., J.K., the Alzheimer center Amsterdam is part of the neurodegeneration research program of L.Fr, A.M.H., J.V., L.H., G.H., N.Sca, M.H.K., M.Y., H.Ho, W.M.v.d.F., M.Hui, N.M.v.S., Amsterdam Neuroscience. The Alzheimer Center Amsterdam is supported by Stichting N.J.A., J.D., M.Sche, A.K.S., C.G., N.B., O.H., P.B., A.H., T.K., J.Wilf, P.F., P.R., P.Sa, P.Sc, Alzheimer Nederland and Stichting VUmc fonds. The clinical database structure was M.Hul, N.T., I.E.J., A.T.H., B.G.N., C.V.B., E.S., R.V., S.E., P.A., A.Ru, and J.C.L. PGC- developed with funding from Stichting Dioraphte. Genotyping of the Dutch case-control ALZ: Sample contribution. I.E.J., A.Ro, I.Sa, D.Aa, G.Se, S.B.S., S.D., D.P., S.H., I.K.K., N. samples was performed in the context of EADB (European Alzheimer DNA biobank) L.P., C.A.R., and O.A.A. Analysis: S.Ha, I.K.K., and I.E.J. Study supervision/management: funded by the JPco-fuND FP-829-029 (ZonMW project number 733051061). 100-Plus O.A.A., C.M.v.D., and D.P. AD and GBCS: Sample contribution. H.Z., S.K., I.S., and K.B. study: We are grateful for the collaborative efforts of all participating centenarians and Analysis: N.M.S. and A.Z. Study supervision/management: I.S.k., A.Z., and K.B.l. NxC: their family members and/or relations. This work was supported by Stichting Alzheimer Sample contribution. A.C.A., M.T.M., M.S.R., and C.An. Nederland (WE09.2014-03), Stichting Diorapthe, horstingstuit foundation, Memorabel (ZonMW project number 733050814, 733050512) and Stichting VUmc Fonds. Geno- typing of the 100-Plus Study was performed in the context of EADB (European Alz- Competing interests heimer DNA biobank) funded by the JPco-fuND FP-829-029 (ZonMW project number The authors declare no competing interests. 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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. © The Author(s) 2021 Itziar de Rojas 1,2,306, Sonia Moreno-Grau1,2,306, Niccolo Tesi3,4,5,306, Benjamin Grenier-Boley6,306, Victor Andrade7,8,306, Iris E. Jansen3,9,306, Nancy L. Pedersen10, Najada Stringa 11, Anna Zettergren 12, Isabel Hernández1,2, Laura Montrreal1, Carmen Antúnez13, Anna Antonell14, Rick M. Tankard 15, Joshua C. 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Satizabal 52,85,86, Clive Holmes87, Dolores Buiza-Rueda2,88, Dag Aarsland 89,90, Dan Rujescu58, Daniel Alcolea 2,24, Daniela Galimberti 80,91, David Wallon 92, Davide Seripa93, Edna Grünblatt 94,95,96, Efthimios Dardiotis97, Emrah Düzel98,99, Elio Scarpini80,91, Elisa Conti100, Elisa Rubino101, Ellen Gelpi102,103, Eloy Rodriguez-Rodriguez 2,39, Emmanuelle Duron104,105,106, Eric Boerwinkle107,108, Evelyn Ferri65, Fabrizio Tagliavini109, Fahri Küçükali 81,82,83, Florence Pasquier 110,111, Florentino Sanchez-Garcia112, Francesca Mangialasche113, Frank Jessen54,114,115, Gaël Nicolas 73, Geir Selbæk 116,117,118, Gemma Ortega1,2, Geneviève Chêne75,76, Georgios Hadjigeorgiou119, Giacomina Rossi109, Gianfranco Spalletta120,121, Giorgio Giaccone109, Giulia Grande122, Giuliano Binetti123,124, Goran Papenberg122, Harald Hampel125, Henri Bailly106,126, Henrik Zetterberg 127,128,129,130, Hilkka Soininen 131,132, Ida K. Karlsson10,133, Ignacio Alvarez 37,38, Ildebrando Appollonio100,134, Ina Giegling58, Ingmar Skoog12, Ingvild Saltvedt 135,136, Innocenzo Rainero137, Irene Rosas Allende26,138, Jakub Hort139,140, Janine Diehl-Schmid141, Jasper Van Dongen 81,82, Jean-Sebastien Vidal 106,126, Jenni Lehtisalo131,142, Jens Wiltfang143,144,145, 10 NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 ARTICLE Jesper Qvist Thomassen56, Johannes Kornhuber 146, Jonathan L. Haines 147,148, Jonathan Vogelgsang 143,149, Juan A. Pineda 23, Juan Fortea2,24, Julius Popp150,151,152, Jürgen Deckert153, Katharina Buerger154,155, Kevin Morgan 156, Klaus Fließbach8, Kristel Sleegers 81,82,83, Laura Molina-Porcel14,102, Lena Kilander157, Leonie Weinhold158, Lindsay A. Farrer 159, Li-San Wang44, Luca Kleineidam7,8, Lucia Farotti160, Lucilla Parnetti160, Lucio Tremolizzo100,134, Lucrezia Hausner161, Luisa Benussi124, Lutz Froelich161, M. Arfan Ikram 162, M. Candida Deniz-Naranjo112, Magda Tsolaki 163, Maitée Rosende-Roca1,2, Malin Löwenmark157, Marc Hulsman3,4, Marco Spallazzi164, Margaret A. Pericak-Vance 70, Margaret Esiri165, María Bernal Sánchez-Arjona22, Maria Carolina Dalmasso7, María Teresa Martínez-Larrad60,61, Marina Arcaro91, Markus M. Nöthen166, Marta Fernández-Fuertes23, Martin Dichgans 154,155,167, Martin Ingelsson157, Martin J. Herrmann153, Martin Scherer168, Martin Vyhnalek139,140, Mary H. Kosmidis169, Mary Yannakoulia170, Matthias Schmid54,158, Michael Ewers 154,155, Michael T. Heneka8,54, Michael Wagner 8,54, Michela Scamosci171, Miia Kivipelto113,172,173,174, Mikko Hiltunen175, Miren Zulaica2,33, Montserrat Alegret1,2, Myriam Fornage176, Natalia Roberto1, Natasja M. van Schoor11, Nazib M. Seidu12, Nerisa Banaj120, Nicola J. Armstrong15, Nikolaos Scarmeas177,178, Norbert Scherbaum179, Oliver Goldhardt141, Oliver Hanon106,126, Oliver Peters180,181, Olivia Anna Skrobot182, Olivier Quenez 71, Ondrej Lerch139,140, Paola Bossù 183, Paolo Caffarra184, Paolo Dionigi Rossi65, Paraskevi Sakka185, Per Hoffmann166,186, Peter A. Holmans 17, Peter Fischer187, Peter Riederer188, Qiong Yang 53, Rachel Marshall17, Rajesh N. Kalaria189,190, Richard Mayeux191,192,193, Rik Vandenberghe194,195, Roberta Cecchetti171, Roberta Ghidoni124, Ruth Frikke-Schmidt56,57, Sandro Sorbi66,67, Sara Hägg 10, Sebastiaan Engelborghs196,197,198,199, Seppo Helisalmi200, Sigrid Botne Sando201,202, Silke Kern12, Silvana Archetti203, Silvia Boschi137, Silvia Fostinelli124, Silvia Gil1, Silvia Mendoza204, Simon Mead205, Simona Ciccone65, Srdjan Djurovic 206,207, Stefanie Heilmann-Heimbach166, Steffi Riedel-Heller208, Teemu Kuulasmaa175, Teodoro del Ser209, Thibaud Lebouvier110,111, Thomas Polak153, Tiia Ngandu113,142, Timo Grimmer141, Valentina Bessi 66,210, Valentina Escott-Price 17,211, Vilmantas Giedraitis 157, Vincent Deramecourt110,111, Wolfgang Maier8,54, Xueqiu Jian 85, Yolande A. L. Pijnenburg3, EADB contributors*, The GR@ACE study group*, DEGESCO consortium*, IGAP (ADGC, CHARGE, EADI, GERAD)*, PGC-ALZ consortia*, Patrick Gavin Kehoe 181, Guillermo Garcia-Ribas40, Pascual Sánchez-Juan 2,39, Pau Pastor 37,38, Jordi Pérez-Tur 2,212,213, Gerard Piñol-Ripoll34,35, Adolfo Lopez de Munain 2,32,33,214, Jose María García-Alberca 2,204, María J. Bullido 2,30,215,216, Victoria Álvarez26,138, Alberto Lleó 2,24, Luis M. Real 23,217, Pablo Mir2,88, Miguel Medina 2,21, Philip Scheltens3, Henne Holstege 3,4, Marta Marquié1,2, María Eugenia Sáez 19, Ángel Carracedo18,218, Philippe Amouyel 6, Gerard D. Schellenberg44, Julie Williams 17,50, Sudha Seshadri 52,85,219, Cornelia M. van Duijn 162,220, Karen A. Mather 221,222, Raquel Sánchez-Valle14, Manuel Serrano-Ríos60,61, Adelina Orellana1,2, Lluís Tárraga1,2, Kaj Blennow 127,128, Martijn Huisman11,223, Ole A. Andreassen 224,225, Danielle Posthuma9, Jordi Clarimón2,24,307, Mercè Boada 1,2,307, Wiesje M. van der Flier 3,307, Alfredo Ramirez 7,8,54,226,307, Jean-Charles Lambert 6,307, Sven J. van der Lee 3,4,307 ✉ & Agustín Ruiz 1,2,307 ✉ 1 Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain. 2CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain. 3 Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. 4Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. 5Delft Bioinformatics Lab, Delft Univeristy of Technology, Delft, The Netherlands. 6 Univ. Lille, Inserm, Institut Pasteur de Lille, CHU Lille, U1167-Labex DISTALZ-RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France. 7Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne, Germany. 8Department of Neurodegenerative diseases and Geriatric Psychiatry, University Clinic Bonn, Bonn, Germany. 9 Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands. 10Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. 11Amsterdam NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications 11 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 UMC-Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands. 12Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AgeCap), University of Gothenburg, Gothenburg, Sweden. 13Unidad de Demencias, Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain. 14Alzheimer’s disease and other cognitive disorders unit. Service of Neurology, Hospital Clínic of Barcelona. Institut d’Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain. 15Mathematics and Statistics, Murdoch University, Perth, WA, Australia. 16Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA. 17Division of Psychological Medicine and Clinial Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK. 18Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Santiago de Compostela, Spain. 19CAEBI, Centro Andaluz de Estudios Bioinformáticos, Sevilla, Spain. 20UFIEC, Instituto de Salud Carlos III, Madrid, Spain. 21CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain. 22Unidad de Demencias, Servicio de Neurología y Neurofisiología, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain. 23Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario de Valme, Sevilla, Spain. 24Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain. 25Servicio de Neurología, Hospital Universitario Central de Asturias, Oviedo, Spain. 26Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain. 27 Departamento de Medicina, Universidad de Oviedo, Oviedo, Spain. 28Department of Neurology, La Paz University Hospital, Instituto de Investigación Sanitaria del Hospital Universitario La Paz, IdiPAZ, Madrid, Spain. 29Hospital La Paz Institute for Health Research, IdiPAZ, Madrid, Spain. 30Universidad Autónoma de Madrid, Madrid, Spain. 31Departamento de Especialidades Quirúrgicas, Bioquímicas e Inmunología, School of Medicine, University of Málaga, Málaga, Spain. 32Department of Neurology, Hospital Universitario Donostia, San Sebastian, Spain. 33Neurosciences Area, Instituto Biodonostia, San Sebastian, Spain. 34Unitat Trastorns Cognitius, Hospital Universitari Santa Maria de Lleida, Lleida, Spain. 35Institut de Recerca Biomedica de Lleida (IRBLLeida), Lleida, Spain. 36Servei de Neurologia, Hospital Universitari i Politècnic La Fe, Valencia, Spain. 37 Fundació Docència i Recerca MútuaTerrassa, Terrassa, Barcelona, Spain. 38Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain. 39Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and IDIVAL), Santander, Spain. 40Hospital Universitario Ramon y Cajal, IRYCIS, Madrid, Spain. 41Karolinska Institutet, Center for Alzheimer Research, Department NVS, Division of Neurogeriatrics, Stockholm, Sweden. 42Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital-Solna, Stockholm, Sweden. 43Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. 44Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. 45Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy. 46BT-CIEN, Madrid, Spain. 47Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy. 48Faculty of Medicine, University of Lisbon, Lisbon, Portugal. 49 Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands. 50UK Dementia Research Institute at Cardiff, Cardiff University, Cardiff, UK. 51Department of Neurology, La Paz University Hospital, Madrid, Spain. 52Department of Neurology, Boston University School of Medicine, Boston, MA, USA. 53Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA. 54German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. 55A.I Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland. 56Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark. 57Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. 58 Martin-Luther-University Halle-Wittenberg, University Clinic and Outpatient Clinic for Psychiatry, Psychotherapy and Psychosomatics, Halle (Saale), Germany. 59Department of Neurology, University of Bonn, Bonn, Germany. 60Instituto de Investigación Sanitaria, Hospital Clínico San Carlos (IdISSC), Madrid, Spain. 61Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain. 62Haugesund Hospital, Helse Fonna, Department of Research and Innovation, Haugesund, Norway. 63University of Bergen, Institute of Clinical Medicine (K1), Bergen, Norway. 64Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy. 65Geriatic Unit, Fondazione Cà Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy. 66Department of Neuroscience, Psychology, Drug Research and Child Health University of Florence, Florence, Italy. 67IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy. 68Department of Clinical Biochemistry, Herlev Gentofte Hospital, Herlev, Denmark. 69Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA. 70John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA. 71Normandie Univ, UNIROUEN, Inserm U1245, CHU Rouen, Department of Genetics and CNR-MAJ, FHU G4 Génomique, F-76000 Rouen, France. 72Institute of Neurology, Catholic University of the Sacred Heart, School of Medicine, Milan, Italy. 73Hospital de Cabueñes, Gijón, Spain. 74 Servicio de Neurología, Hospital Universitario de Gran Canaria Dr.Negrín, Las Palmas, Spain. 75Inserm, Bordeaux Population Health Research Center, UMR 1219, Univ. Bordeaux, ISPED, CIC 1401-EC, Univ Bordeaux, Bordeaux, France. 76CHU de Bordeaux, Pole de Santé Publique, Bordeaux, France. 77Instituto de Medicina Molecular João lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal. 78Unit of Clinical Pharmacology, University Hospital of Cagliari, Cagliari, Italy. 79Department of Psychology, University of California—Riverside, Riverside, CA, USA. 80 University of Milan, Dino Ferrari Center, Milan, Italy. 81VIB Center for Molecular Neurology, Antwerp, Belgium. 82Laboratory of Neurogenetics, Institute Born-Bunge, Antwerp, Belgium. 83Department of Biomedical Sciences, University of Antwerp., Antwerp, Belgium. 84Insititute for Regenerative Medicine, University of Zürich, Zürich, Switzerland. 85Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX, USA. 86Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX, USA. 87Division of Clinical Neurosciences, School of Medicine, University of Southampton, Southampton, UK. 88Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain. 89 Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK. 90Centre of Age- Related Medicine, Stavanger University Hospital, Stavanger, Norway. 91Fondazione IRCCS Ca’ Granda, Ospedale Policlinico, Milan, Italy. 92 Normandie Univ, UNIROUEN, Inserm U1245, CHU Rouen, Department of Neurology and CNR-MAJ, FHU G4 Génomique, F-76000 Rouen, France. 93Complex Structure of Geriatrics, Department of Medical Sciences Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy. 94Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich (PUK), University of Zurich, Zurich, Switzerland. 95Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland. 96Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland. 97School of Medicine, University of Thessaly, Larissa, Greece. 98 German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany. 99Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany. 100School of Medicine and Surgery, University of Milano-Bicocca and Milan Center for Neuroscience, Milan, Italy. 101Department of Neuroscience and Mental Health, AOU Città della Salute e della Scienza di Torino, Torino, Italy. 102 Neurological Tissue Bank of the Biobanc-Hospital Clinic-IDIBAPS, Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain. 103 Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria. 104APHP, Hôpital Brousse, equipe INSERM 1178, MOODS, Villejuif, France. 105Université Paris-Saclay, UVSQ, Inserm, CESP, Team MOODS, Le Kremlin-Bicêtre, 12 NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 ARTICLE Paris, France. 106APHP, Hôpital Broca, Paris, France. 107School of Public Health, Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA. 108Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA. 109Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy. 110Inserm U1172, CHU, DISTAlz, LiCEND, Univ Lille, Lille, France. 111CHU CNR-MAJ, Lille, France. 112 Servicio de Inmunología, Hospital Universitario de Gran Canaria Dr. Negrín, Las Palmas de Gran Canaria, Spain. 113Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden. 114 Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne, Germany. 115Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany. 116Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway. 117Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway. 118Institute of Clinical Medicine, University of Oslo, Oslo, Norway. 119Department of Neurology, Medical School, University of Cyprus, Nicosia, Cyprus. 120 Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy. 121Beth K. and Stuart C. Yudofsky Division of Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA. 122Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden. 123MAC—Memory Clinic, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. 124Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. 125Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Paris, France. 126EA 4468, Sorbonne Paris Cité, Université Paris Descartes, Paris, France. 127Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden. 128Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden. 129Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK. 130UK Dementia Research Institute at UCL, London, UK. 131Institute of Clinical Medicine Neurology, University of Eastern Finland, Kuopio, Finland. 132 Neurocenter, neurology, Kuopio University Hospital, Kuopio, Finland. 133Institute for Gerontology and Aging Research Network—Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden. 134Neurology Unit, ‘San Gerardo’ hospital, Monza, Italy. 135 Department of Geriatrics, Clinic of Medicine, St Olavs Hospital, University Hospital of Trondheim, Trondheim, Norway. 136Department of Neuromedicine and Movement Science, Norwegian University of Science and Technhology (NTNU), Trondheim, Norway. 137Department of Neuroscience “Rita Levi Montalcini”, University of Torino, Torino, Italy. 138Laboratorio de Genética, Hospital Universitario Central de Asturias, Oviedo, Spain. 139Memory Clinic, Department of Neurology, 2nd Faculty of Medicine and Motol University Hospital, Charles University, Prague, Czech Republic. 140International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic. 141Department of Psychiatry and Psychotherapy, School of Medicine Klinikum rechts der Isar, Technical University of Munich, Munich, Germany. 142Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland. 143Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Goettingen, Germany. 144German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany. 145Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal. 146Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany. 147Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA. 148Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA. 149Translational Neuroscience Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, USA. 150Department of Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland. 151University of Zürich, Zürich, Switzerland. 152Old age Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland. 153Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital, Wuerzburg, Germany. 154Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany. 155German Center for Neurodegenerative Diseases (DZNE), Munich, Germany. 156Schools of Life Sciences and Medicine, University of Nottingham, Nottingham, UK. 157Department of Public Health and Caring Sciences/Geriatrics, Uppsala, Sweden. 158Institute of Medical Biometry, Informatics and Epidemiology, University Hospital of Bonn, Bonn, Germany. 159Departments of Medicine (Biomedical Genetics), Neurology, Ophthalmology, Epidemiology, and Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, USA. 160Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, University of Perugia, Perugia, Italy. 161Department of Geriatric Psychiatry, Central Institute for Mental Health Mannheim, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany. 162Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands. 1631st Department of Neurology Aristotle University of Thessaloniki, Thessaloniki, Greece. 164Azienda Ospedaliero-Universitaria, Parma, Italy. 165Nuffield Department of Clinical Neurosciences, Oxford, UK. 166Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany. 167Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. 168Department of Primary Medical Care, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany. 169Laboratory of Cognitive Neuroscience, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece. 170Department of Nutrition and Dietetics, Harokopio University, Athens, Greece. 171Institute of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy. 172Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland. 173Neuroepidemiology and Ageing Research Unit, School of Public Health, Imperial College London, London, UK. 174Stockholms Sjukhem, Research & Development Unit, Stockholm, Sweden. 175Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland. 176Brown Foundation Institute of Molecular Medicine, University of Texas Health Sciences Center at Houston, Houston, TX, USA. 1771st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, Medical School, Athens, Greece. 178Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, The Gertrude H. Sergievsky Center, Depatment of Neurology, Columbia University, New York, NY, USA. 179LVR-Hospital Essen, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Duisburg-Essen, Essen, Germany. 180Department of Psychiatry and Psychotherapy and Experimental and Clinical Research Center (ECRC), Charité-Universitätsmedizin Berlin, Berlin, Germany. 181German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany. 182Bristol Medical School (THS), University of Bristol, Southmead Hospital, Bristol, UK. 183Experimental Neuro-psychobiology Laboratory, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy. 184Unit of Neuroscience, DIMEC, University of Parma, Parma, Italy. 185 Athens Association of Alzheimer’s disease and Related Disorders, Athens, Greece. 186Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland. 187Department of Psychiatry, Social Medicine Center East- Donauspital, Vienna, Austria. 188Center of Mental Health, Clinic and Policlinic of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, Würzburg, Germany. 189 Translational and Clincial Research Institute, Newcastle University, Newcastle upon Tyne, UK. 190Campus for Ageing anf Vitality, Newcastle upon Tyne, UK. 191Taub Institute on Alzheimer’s Disease and the Aging Brain, Department of Neurology, Columbia University, New York, NY, USA. 192 Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA. 193Department of Neurology, Columbia University, New York, NY, USA. 194Laboratory for Cognitive Neurology, Department of Neurosciences, University of Leuven, Leuven, Belgium. 195Neurology Department, University Hospitals Leuven, Leuven, Belgium. 196Center for Neurosciences, Vrije Universiteit Brussel (VUB), Brussels, Belgium. 197Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium. 198Institute Born-Bunge, University of Antwerp, Antwerp, Belgium. 199Department of Neurology, VUB University Hospital Brussels (UZ Brussel), Brussels, Belgium. 200Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland. 201Department of Neurology and Clinical Neurophysiology, University Hospital of NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications 13 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 Trondheim, Trondheim, Norway. 202Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway. 203Department of Laboratory Diagnostics, III Laboratory of Analysis, Brescia Hospital, Brescia, Italy. 204Alzheimer Research Center & Memory Clinic, Andalusian Institute for Neuroscience, Málaga, Spain. 205MRC Prion Unit at UCL, Institute of Prion Diseases, London, UK. 206Department of Medical Genetics, Oslo University Hospital, Oslo, Norway. 207NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway. 208Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany. 209Department of Neurology/CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain. 210Azienda Ospedaliero-Universitaria Careggi Largo Brambilla, Florence, Italy. 211UKDRI Cardiff, Cardiff University, Cardiff, UK. 212Unitat de Genètica Molecular, Institut de Biomedicina de València-CSIC, Valencia, Spain. 213Unidad Mixta de Neurologia Genètica, Instituto de Investigación Sanitaria La Fe, Valencia, Spain. 214Department of Neurosciences, Faculty of Medicine and Nursery, University of the Basque Country, San Sebastián, Spain. 215 Centro de Biología Molecular Severo Ochoa (UAM-CSIC), Madrid, Spain. 216Instituto de Investigacion Sanitaria ‘Hospital la Paz’ (IdIPaz), Madrid, Spain. 217Departamento de Especialidades Quirúrgicas, Bioquímica e Inmunología. Facultad de Medicina, Universidad de Málaga, Málaga, Spain. 218Fundación Pública Galega de Medicina Xenómica-CIBERER-IDIS, Santiago de Compostela, Spain. 219Framingham Heart Study, Framingham, MA, USA. 220Nuffield Department of Population Health, University of Oxford, Oxford, UK. 221Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia. 222Neuroscience Research Australia, Sydney, NSW, Australia. 223Department of Sociology, VU University, Amsterdam, The Netherlands. 224NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway. 225Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. 226Department of Psychiatry, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX, USA. 306These authors contributed equally: Itziar de Rojas, Sonia Moreno-Grau, Niccolo Tesi, Benjamin Grenier-Boley, Victor Andrade, Iris E. Jansen. 307These authors jointly supervised this work: Jordi Clarimón, Mercè Boada, Wiesje M. van der Flier, Alfredo Ramirez, Jean-Charles Lambert, Sven J. van der Lee, Agustín Ruiz. *Lists of authors and their affiliations appears at the end of the paper. ✉email: s.j.vanderlee@amsterdamumc.nl; aruiz@fundacioace.org EADB contributors A. David Smith227,228, Aldo Saenz229, Alessandra Bizzarro230, Alessandra Lauria230, Alessandro Vacca137, Alina Solomon113,131, Anna Anastasiou163, Anna Richardson231,232, Anne Boland233, Anne Koivisto234,235, Antonio Daniele236, Antonio Greco237, Arnaoutoglou Marianthi163, Bernadette McGuinness238, Bertrand Fin233, Camilla Ferrari66, Carlo Custodero239, Carlo Ferrarese100,134, Carlos Ingino240,241, Carlos Mangone240,242, Carlos Reyes Toso240, Carmen Martínez26,243, Carolina Cuesta244,245, Carolina Muchnik240, Catharine Joachim246, Cecilia Ortiz247, Céline Besse233, Charlotte Johansson41,42, Chiara Paola Zoia100, Christoph Laske248,249, Costas Anastasiou170, Dana Lis Palacio250,251, Daniel G. Politis244,245,252, Daniel Janowitz253, David Craig238, David M. Mann254, David Neary231, Deckert Jürgen153, Delphine Daian233, Diyana Belezhanska255, Eduardo Kohler256, Eduardo M. Castaño257,258, Effrosyni Koutsouraki163, Elena Chipi160, Ellen De Roeck196, Emanuele Costantini236, Emma R. L. C. Vardy259, Fabrizio Piras120, Fausto Roveta137, Federica Piras120, Federico Ariel Prestia245,257, Francesca Assogna120, Francesca Salani183, Gessica Sala100, Giordano Lacidogna236, Gisela Novack257,258, Gordon Wilcock260, Håkan Thonberg41,42, Heike Kölsch261, Heike Weber153, Henning Boecker54,262, Ignacio Etchepareborda250,251, Irene Piaceri66, Jaakko Tuomilehto142,263,264,265, Jaana Lindström142, Jan Laczo139,140, Janet Johnston238, Jean-François Deleuze233, Jenny Harris231, Jonathan M. Schott266, Josef Priller181,267, Juan Ignacio Bacha247, Julie Snowden231,232, Julieta Lisso268, Kalina Yonkova Mihova269, Latchezar Traykov255, Laura Morelli257,258, Luis Ignacio Brusco240,241, Malik Rainer253, Mari Takalo175, Maria Bjerke196,270, Maria Del Zompo47,271, Maria Serpente80, Mariana Sanchez Abalos 272, Mario Rios229, Markku Peltonen142, Martin J. Herrman153, Mary H. Kosmidis169, Matias Kohler250,256, Matias Rojo240, Matthew Jones231,273, Michela Orsini236, Nancy Medel268, Natividad Olivar240, Nick C. Fox266,274, Nicola Salvadori160, Nigel M. Hooper232, Pablo Galeano244,257,258, Patricia Solis268, Patrizia Bastiani171, Patrizia Mecocci171, Peter Passmore238, Reinhard Heun261, Riitta Antikainen275,276,277, Robert Olaso233, Robert Perneczky167,278,279,280, Sandra Germani240, Sara López-García2,39, Seth Love182,281, Shima Mehrabian255, Silvia Bagnoli66, Silvia Kochen268, Simona Andreoni100, Stefan Teipel282,283, Stephen Todd238, Stuart Pickering-Brown254, Teemu Natunen175, Thomas Tegos163, Tiina Laatikainen172,284,285, Timo Strandberg275,286, Tuomo M. Polvikoski189,190, Vaclav Matoska287, Valentina Ciullo120, Valeria Cores244,245,252, Vincenzo Solfrizzi239, Viviana Lisetti160 & Zulma Sevillano268 14 NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 ARTICLE 227 University of Oxford (OPTIMA), Oxford, UK. 228OPTIMA, Department of Pharmacology, University of Oxford, Oxford, UK. 229Dirección de Atención de Adultos Mayores del Min., Salud Desarrollo Social y Deportes de la Pcia. de Mendoza, Mendoza, Argentina. 230Geriatrics Unit Fondazione Policlinico A. Gemelli IRCCS, Rome, Italy. 231Cerebral Function Unit, Greater Manchester Neurosciences Centre, Salford Royal Hospital, Salford, UK. 232Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK. 233Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, F-91057 Evry, France. 234Department of Neurology, Kuopio University Hospital, Kuopio, Finland. 235Insitute of Clinical Medicine-Neurology, University of Eastenr Finland, Kuopio, Finland. 236Institute of Neurology, Catholic University of Sacred Heart, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy. 237Research Laboratory, Complex Structure of Geriatrics, San Giovanni Rotondo, Fondazione IRCCS Casa Sollievo della Sofferenza, Foggia, Italy. 238Centre for Public Health, School of Medicine, Queen’s University Belfast, Belfast, UK. 239Clinica Medica “Frugoni” and Geriatric Medicine-Memory Unit, University of Bari Aldo Moro, Bari, Italy. 240CENECON-FMED-UBA, Buenos Aires, Argentina. 241ENERI, Vienna, Austria. 242Htal Santojani, Buenos Aires, Argentina. 243Servicio de Neurología, Hospital de Cabueñes, Gijón, Spain. 244UBA, Buenos Aires, Argentina. 245HIGA Eva Perón, Billinghurst, Argentina. 246University of Oxford, Oxford, UK. 247Neurología Clinica, Madrid, Spain. 248German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany. 249Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany. 250Hospital Dr. Lucio Molas, Santa Rosa, Argentina. 251Fundacion Ayuda Enfermo Renal y Alta Complejidad (FERNAC), Santa Rosa, Argentina. 252CONICET, Buenos Aires, Argentina. 253Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilian University Munich, Munich, Germany. 254Faculty of Medical and Human Sciences, Institute of Brain, Behaviour and Mental Health, Manchester, UK. 255Clinic of Neurology UH ‘Alexandrovska’, Medical University—Sofia, Sofia, Bulgaria. 256Fundacion Sinapsis, Santa Rosa, Argentina. 257Laboratory of Brain Aging and Neurodegeneration- FIL, Buenos Aires, Argentina. 258IIBBA (CONICET), Buenos Aires, Argentina. 259Salford Royal NHS Foundation Trust, Salford, England. 260Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK. 261Department of Psychiatry, University of Bonn, Bonn, Germany. 262Department of Radiology, University Hospital Bonn, Bonn, Germany. 263Department of Public Health, University of Helsinki, Helsinki, Finland. 264National School of Public Health, Madrid, Spain. 265South Ostrobothnia Central Hospital, Seinäjoki, Finland. 266Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK. 267 Department of Neuropsychiatry, Charité, Berlin, Germany. 268ENYS (Estudio en Neurociencias y Sistemas Complejos) CONICET-Hospital El Cruce ‘Nestor Kirchner’-UNAJ, Buenos Aires, Argentina. 269Molecular Medicine Center, Department of Medical chemistry and biochemistry, Medical University of Sofia, Sofia, Bulgaria. 270Laboratory of Neurochemistry, UZ Brussel, Brussel, Belgium. 271Unit of Clinical Pharmacology, Teaching Hospital of Cagliari, AOUCA, Cagliari, Italy. 272Programa del Adulto Mayor-Min, Salud de la Pcia. de Jujuy, San Salvador de Jujuy, Argentina. 273Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK. 274UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, University College London, London, UK. 275Center for Life Course Health Research, University of Oulu, Oulu, Finland. 276Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland. 277Oulu City Hospital, Oulu, Finland. 278 German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany. 279Department of Psychiatry and Psychotherapy, University Hospital LMU Munich, Munich, Germany. 280Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK. 281University of Bristol Institute of Clinical Neurosciences, School of Clinical Sciences, Frenchay Hospital, Bristol, UK. 282 German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany. 283Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany. 284Finnish Institute for Health and Welfare, Helsinki, Finland. 285Joint Municipal Authority for North Karelia Social and Health Services (Siun Sote), Joensuu, Finland. 286Helsinki University Hospital, University of Helsinki, Helsinki, Finland. 287Department of Clinical Biochemistry, Hematology and Immunology, Na Homolce Hospital, Prague, Czech Republic. The GR@ACE study group C. Abdelnour1,2, N. Aguilera1, E. Alarcon1,31, M. Alegret1,2, A. Benaque1, M. Boada1,2, M. Buendia1, P. Cañabate1,2, A. Carracedo18,218, A. Corbatón-Anchuelo6, I. de Rojas1, S. Diego1, A. Espinosa1,2, A. Gailhajenet1, P. García-González1, S. Gil1, M. Guitart1, A. González-Pérez19, I. Hernández1,2, M. Ibarria1, A. Lafuente1, J. Macias23, O. Maroñas18, E. Martín1, M. T. Martínez62, M. Marquié1, A. Mauleón1, L. Montrreal1, S. Moreno-Grau1,2, M. Moreno1, A. Orellana1, G. Ortega1,2, A. Pancho1, E. Pelejá1, A. Pérez-Cordon1, J. A. Pineda23, S. Preckler1, I. Quintela31, L. M. Real8,31, M. Rosende-Roca1, A. Ruiz1,2, M. E. Sáez19, A. Sanabria1,2, M. Serrano-Rios61, O. Sotolongo-Grau1, L. Tárraga1,2, S. Valero1,2 & L. Vargas1 DEGESCO consortium A. D. Adarmes-Gómez2,22, E. Alarcón-Martín1,31, M. D. Alonso288, I. Álvarez37,38, V. Álvarez26,138, G. Amer-Ferrer289, M. Antequera13, C. Antúnez13, M. Baquero36, M. Bernal22, R. Blesa2,24, M. Boada1,2, D. Buiza-Rueda2,22, M. J. Bullido2,215,216, J. A. Burguera36, M. Calero2,21,40, F. Carrillo2,22, M. Carrión-Claro2,22, M. J. Casajeros290, J. Clarimón2,24, J. M. Cruz-Gamero31, M. M. de Pancorbo291, I. de Rojas1,2, T. del Ser216, M. Diez-Fairen37,38, R. Escuela2,22, L. Garrote-Espina2,22, J. Fortea2,24, E. Franco-Macías22, A. Frank-García2,29,216, J. M. García-Alberca204, S. Garcia Madrona40, G. Garcia-Ribas40, P. Gómez-Garre2,22, I. Hernández1,2, S. Hevilla204, S. Jesús2,22, M. A. Labrador Espinosa2,22, C. Lage2,39, A. Legaz13, A. Lleó2,24, A. Lopez de Munain32,33, S. López-García2,39, D. Macias-García2,22, S. Manzanares289,292, M. Marín22, J. Marín-Muñoz13, T. Marín204, M. Marquié1,2, A. Martín Montes2,29,215, B. Martínez13, C. Martínez26,243, NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications 15 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22491-8 V. Martínez13, P. Martínez-Lage Álvarez293, M. Medina2,216, M. Mendioroz Iriarte294, M. Menéndez-González25,26, P. Mir2,22, J. L. Molinuevo295, L. Montrreal1, A. Orellana1, P. Pastor37,38, J. Pérez Tur2,212,213, T. Periñán-Tocino2,22, R. Pineda-Sanchez2,22, G. Piñol-Ripoll2,34,35, A. Rábano2,21,46, D. Real de Asúa296, S. Rodrigo22, E. Rodríguez-Rodríguez2,39, J. L. Royo31, A. Ruiz1,2, R. Sanchez del Valle Díaz14, P. Sánchez-Juan2,39, I. Sastre2,215, O. Sotolongo-Grau1, S. Valero1,2, M. P. Vicente13, R. Vigo-Ortega2,22 & L. Vivancos13 288 Servei de Neurologia, Hospital Clínic Universitari de València, València, Spain. 289Department of Neurology, Hospital Universitario Son Espases, Palma, Spain. 290Hospital Universitario Ramón y Cajal, Madrid, Spain. 291BIOMICs, País Vasco, Centro de Investigación Lascaray, Universidad del País Vasco UPV/EHU, Leioa, Spain. 292Fundación para la Formación e Investigación Sanitarias de la Región de Murcia, El Palmar, Spain. 293 Fundación CITA-alzheimer, Centro de Investigacio´n y Terapias Avanzadas, San Sebastián, Spain. 294Navarrabiomed, Pamplona, Spain. 295 Barcelona beta Brain Research Center–Fundació Pasqual Maragall, Barcelona, Spain. 296Hospital Universitario La Princesa, Madrid, Spain. IGAP (ADGC, CHARGE, EADI, GERAD) C. Macleod297, C. McCracken298, Carol Brayne299, Catherine Bresner17, Detelina Grozeva17, Eftychia Bellou17, Ewen W. Sommerville17, F. Matthews300, Ganna Leonenko17, Georgina Menzies50, Gill Windle297, Janet Harwood17, Judith Phillips301, K. Bennett302, Lauren Luckuck17, Linda Clare303, Robert Woods304, Salha Saad17 & Vanessa Burholt305 297 School of Health Sciences, Bangor University, Bangor, UK. 298Institute of Psychology, Health and Society, University of Liverpool, Liverpool, England. 299School of Clinical Medicine, Cambridge Institute of Public Health, University of Cambridge, Cambridge, England. 300Faculty of Medicine, Institute of Health and Society, University of Newcastle, Callaghan, NSW, Australia. 301Dementia Studies, University of Stirling, Stirling, Scotland. 302School of Psychology, University of Liverpool, Liverpool, England. 303School of Psychology, Centre for Research in Ageing and Cognitive Health (REACH), University of Exeter, Exeter, England. 304Dementia Services Development Centre, Bangor University, Wales, UK. 305 Swansea University, School of Human Sciences, Centre for Innovative Ageing, Swansea, UK. PGC-ALZ consortia Iris E. Jansen3,9, Nancy L. Pedersen10, Arvid Rongve62, Chandra A. Reynolds 79, Dag Aarsland 89,90, Geir Selbæk 116,117,118, Ida K. Karlsson10,133, Ingvild Saltvedt 135,136, Sara Hägg 10, Sigrid Botne Sando201,202, Srdjan Djurovic 206,207, Ole A. Andreassen 224,225, Danielle Posthuma9 16 NATURE COMMUNICATIONS | (2021)12:3417 | https://doi.org/10.1038/s41467-021-22491-8 | www.nature.com/naturecommunications