New insights into the genetic etiology of Alzheimer’s disease and related dementias

Articles https://doi.org/10.1038/s41588-022-01024-z A full list of author and affiliations appears at the end of the paper. AD is the most common form of dementia. The heritability is high, estimated to be between 60% and 80%1. This strong genetic component provides an opportunity to determine the pathophysiological processes in AD and to identify new biological features, new prognostic/diagnostic markers and new therapeutic targets through translational genomics. Characterizing the genetic risk factors in AD is therefore a major objective; with the advent of high-throughput genomic techniques, a large number of putative AD-associated loci/genes have been reported2. However, much of the underlying heritability remains unexplained. Hence, increasing the sample size of genome-wide association studies (GWASs) is an obvious solution that has already been used to characterize new genetic risk factors in other common, complex diseases (e.g., diabetes). GWAS meta-analysis The European Alzheimer & Dementia Biobank (EADB) consortium brings together the various European GWAS consortia already working on AD. A new dataset of 20,464 clinically diagnosed AD cases and 22,244 controls has been collated from 15 European countries. The EADB GWAS results were meta-analyzed with a proxy-AD GWASs of the UK Biobank (UKBB) dataset. The UKBB’s proxy-AD designation is based on questionnaire data in which individuals are asked whether their parents had dementia. This method has been used successfully in the past3 but is less specific than a clinical or pathological diagnosis of AD; hence, we will refer to these cases as proxy AD and related dementia (proxy-ADD). EADB stage I (GWAS meta-analysis) was based on 39,106 clinically diagnosed AD cases, 46,828 proxy-ADD cases (as defined in the Supplementary Note), 401,577 controls (Supplementary Tables 1 and 2) and 21,101,114 variants that passed our quality control (Fig. 1; see Supplementary Fig. 1 for the quantile–quantile plot and genomic inflation factors). We selected all variants with a P value below 1 × 10−5 in stage I. We defined nonoverlapping regions around these variants, excluded the region corresponding to APOE and examined the remaining variants in a large follow-up sample that included AD cases and controls from the ADGC, FinnGen and CHARGE consortia (stage II; 25,392 AD cases and 276,086 controls). A signal was considered as significant on the genome-wide level if it (1) was nominally associated (P ≤ 0.05) in stage II, (2) had the same direction of association in the stage I and II analyses and (3) was associated with the ADD risk with P ≤ 5 × 10−8 in the stage I and stage II meta-analysis. Furthermore, we applied a PLINK clumping procedure4 to define potential independent hits within the stage I results (Methods). After validation by conditional analyses (Supplementary Note and Supplementary Tables 3 and 4), this approach enabled us to define 39 signals in 33 loci already known to be associated with the risk of developing ADD3,5–10 and identify 42 loci defined as new at the time of analysis (Tables 1 and 2, Supplementary Table 5 and Supplementary Figs. 2–29). Of the 42 new loci, 17 had P ≤ 5 × 10−8 in stage I and 25 were associated with P ≤ 5 × 10−8 after follow-up (stage I and stage II meta-analysis, including the ADGC, CHARGE and FinnGen data). We also identified 6 loci with P ≤ 5 × 10−8 in the stage I and stage II analysis but with P > 0.05 in stage II (Supplementary Table 6). It is noteworthy that the magnitude of the associations in stage I did not change substantially if we restricted the analysis to clinically diagnosed AD cases (Supplementary Table 7 and Supplementary Fig. 30). Similarly, none of the signals observed appeared to be especially driven by the UKBB data (Supplementary Table 7 and Supplementary Figs. 2–29). Nine of these loci (APP, CCDC6, GRN, LILRB2, NCK2, TNIP1, TMEM106B, TSPAN14 and SHARPIN) were recently reported in three articles using part of the GWAS data included in our study11–13. We also generated a detailed analysis of the human leukocyte antigen (HLA) locus on the basis of the clinically diagnosed AD cases (Supplementary Tables 8 and 9, Supplementary Figs. 31 and 32 and Supplementary Note). Genetic overlap with other neurodegenerative diseases We tested the association of the lead variants within our new loci with the risk of developing other neurodegenerative diseases or AD-related disorders (Supplementary Fig. 33 and Supplementary Tables 10–12). We also performed more precise colocalization analyses (using Coloc R package, https://cran.r-project.org/web/ packages/coloc/index.html) for five loci known to be associated with Parkinson’s disease (IDUA and CTSB), types of frontotemporal dementia (TMEM106B and GRN) and amyotrophic lateral sclerosis (TNIP1) (Supplementary Tables 13 and 14). The IDUA signal for Parkinson’s disease was independent of the signal in ADD (coloc posterior probability (PP)3 = 99.9%), but we were not able to determine whether the CTSB signals colocalized. The TMEM106B and GRN signals in frontotemporal lobar degeneration with TAR DNA-binding protein (TDP-43) inclusions (frontotemporal lobar New insights into the genetic etiology of Alzheimer’s disease and related dementias Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele. NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 412 Articles NATure GeNeTiCs degeneration TDP) probably share causal variants with ADD (coloc PP4 = 99.8% and coloc PP4 = 80.1%, respectively). Lastly, we were not able to determine whether the TNIP1 signals colocalized for ADD and amyotrophic lateral sclerosis. Pathway analyses Next, we sought to perform a pathway enrichment analysis on the stage I association results to gain better biological understanding of this newly expanded genetic landscape for ADD. Ninety-three gene sets were still statistically significant after correction for multiple testing (q ≤ 0.05; Methods and Supplementary Table 15). As described previously, the most significant gene sets are related to amyloid and tau5; other significant gene sets are related to lipids, endocytosis and immunity (including macrophage and microglial cell activation). When restricting this analysis to the meta-analysis based on the clinically diagnosed AD cases, 54 gene sets were significant (q ≤ 0.05). Of these 54 gene sets, 33 reached q ≤ 0.05 in the stage I analysis and all reached P ≤ 0.05. This indicates that the inclusion of proxy-ADD cases does not cause disease-relevant biological information to be missed and underlines the additional power of this type of analysis. We next performed a single-cell expression enrichment analysis by using the average gene expression per nucleus (Av. Exp.) data in the human Allen Brain Atlas (49,495 nuclei from 8 human brains). Only the microglial expression reached a high level of significance (P = 1.7 × 10−8; Supplementary Table 16); greater expression corresponded to a more significant association with ADD. After adjusting for microglial Av. Exp., the remaining associations became nonsignificant; this indicates that microglial Av. Exp. drives all the other cell-type associations. These results were observed whatever the brain region studied (Supplementary Table 16). A similar result was observed using a mouse single-cell dataset14 (Supplementary Table 17 and Supplementary Note). Lastly, we looked at whether the relationship between an elevated microglia Av. Exp. and a genetic association with the ADD risk was specific to particular biological processes (Supplementary Table 18) by analyzing the interaction between microglia Av. Exp. and pathway membership in MAGMA15. Of the five most significant interaction signals (q ≤ 10−3), two were directly associated with endocytosis processes (GO:0006898 and GO:0031623); this suggested a functional relationship between microglia and endocytosis, which is known to be involved in phagocytosis (Supplementary Table 18). It is noteworthy that we also detected an interaction between GO:1902991 (regulation of amyloid precursor protein (APP) catabolic process) and the gene expression level in microglia (q = 1.4 × 10−3; Supplementary Table 18). Even though these data suggest a functional relationship between microglia and APP/amyloid beta (Aβ) peptide pathways, this observation reinforces the likely involvement of microglial endocytosis in AD, a mechanism that is also strongly involved in APP metabolism16. Of note, there are overall similarities in the interaction effects of human and mouse microglia expression with genes in biological pathways of relevance to the AD genetic risk (Supplementary Table 18 and Supplementary Note). Gene prioritization We next attempted to identify the genes most likely to be responsible for the association signal with ADD at each new locus. To this end, we studied the downstream effects of ADD-associated variants on molecular phenotypes (i.e., expression, splicing, protein expression, methylation and histone acetylation) in various cis-quantitative trait locus (cis-QTL) catalogues from AD-relevant tissues, cell types and brain regions. We investigated the genetic SORT1 CR1 ADAM17 PRKD3 NCK2 BIN1 WDR12 INPP5D MME IDUA CLNK/HS3ST1 RHOH ANKH COX7C TNIP1 RASGEF1C HLA TREM2 CD2AP HS3ST5 UMAD1 ICA1 TMEM106B JAZF1 NME8 SEC61G ZCWPW1/NYAP1 EPHA1 CTSB PTK2B CLU SHARPIN ABCA1 ECHDC3 ANK3 TSPAN14 BLNK PLEKHA1 CELF1/SPI1 MS4A PICALM SORL1 TPCN1 FERMT2 SLC24A4/RIN3 IGH gene cluster SPPL2A ADAM10 APH1B SNX1 CTSH DOC2A KAT8 IL34 MAF PLCG2 FOXF1 PRDM7 WDR81 SCIMP/RABEP1 MYO15A GRN MAPT ABI3 TSPOAP1 ACE ABCA7 KLF16 APOE SIGLEC11 LILRB2 RBCK1 CASS4 SLC2A4RG APP ADAMTS1 0 4 8 12 16 20 24 28 32 36 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Chromosome −log10(P) Fig. 1 | Manhattan plot of the stage i results. P values are two-sided raw P values derived from a fixed-effect meta-analysis. Variants with a P value below 1 × 10−36 are not shown. Loci with a genome-wide significant signal are annotated (known loci in black and new loci in red). Variants in new loci are highlighted in red. The red dotted line represents the genome-wide significance level (P = 5 × 10−8), and the black dotted line represents the suggestive significance level (P = 1 × 10−5). NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 413 Articles NATure GeNeTiCs colocalization between association signals for the ADD risk and those for the molecular phenotypes and the association between the ADD risk and these phenotypes by integrating cis-QTL information into our ADD GWAS. Moreover, we considered the lead variant annotation (the allele frequency, protein-altering effects and nearest protein-coding gene) and a genome-wide, high-content short interfering RNA screen for APP metabolism17. Based on this evidence, we developed a systematic gene prioritization strategy that yielded a total weighted score of between 0 and 100 for each gene (Supplementary Fig. 34 and Supplementary Note). This score was used to compare and prioritize genes in the new loci within 1 Mb upstream and 1 Mb downstream of the lead variants. Genes either were ranked as tier 1 (greater likelihood of being the causal risk gene responsible for the ADD signal) or tier 2 (lower likelihood and the absence of a minimum level of evidence as a causal risk gene) or were not ranked. Table 1 | Summary of association results in the stage i and stage ii analysis for known loci with a genome-wide significant signal Variantachromosome PositionbGenecKnown locus Minor/major allele MAFdOre95% ci P value rs679515 1 207577223 CR1 CR1 T/C 0.188 1.13 1.11–1.15 7.2 × 10−46 rs6733839 2 127135234 BIN1 BIN1 T/C 0.389 1.17 1.16–1.19 6.1 × 10−118 rs10933431 2 233117202 INPP5D INPP5D G/C 0.234 0.93 0.92–0.95 3.6 × 10−18 rs6846529 4 11023507 CLNK CLNK/HS3ST1 C/T 0.283 1.07 1.05–1.08 2.2 × 10−17 rs6605556 6 32615322 HLA-DQA1 HLA G/A 0.161 0.91 0.90–0.93 7.1 × 10−20 rs10947943 6 41036354 UNC5CL TREM2 A/G 0.142 0.94 0.93–0.96 1.1 × 10−9 rs143332484 6 41161469 TREM2 TREM2 T/C 0.013 1.41 1.32–1.50 2.8 × 10−25 rs75932628 6 41161514 TREM2 TREM2 T/C 0.003 2.39 2.09–2.73 2.5 × 10−37 rs60755019 6 41181270 TREML2 TREM2 G/A 0.004 1.55 1.33–1.80 2.1 × 10−8 rs7767350 6 47517390 CD2AP CD2AP T/C 0.271 1.08 1.06–1.09 7.9 × 10−22 rs6966331 7 37844191 EPDR1 NME8 T/C 0.349 0.96 0.94–0.97 4.6 × 10−10 rs7384878 7 100334426 SPDYE3 ZCWPW1/NYAP1 C/T 0.31 0.92 0.91–0.94 1.1 × 10−26 rs11771145 7 143413669 EPHA1 EPHA1 A/G 0.348 0.95 0.93–0.96 3.3 × 10−14 rs73223431 8 27362470 PTK2B PTK2B T/C 0.369 1.07 1.06–1.08 4.0 × 10−22 rs11787077 8 27607795 CLU CLU T/C 0.392 0.91 0.90–0.92 1.7 × 10−44 rs7912495 10 11676714 USP6NL ECHDC3 G/A 0.462 1.06 1.05–1.08 9.7 × 10−19 rs10437655 11 47370397 SPI1 CELF1/SPI1 A/G 0.399 1.06 1.04–1.07 5.3 × 10−14 rs1582763 11 60254475 MS4A4A MS4A A/G 0.371 0.91 0.90–0.92 3.7 × 10−42 rs3851179 11 86157598 EED PICALM T/C 0.358 0.9 0.89–0.92 3.0 × 10−48 rs74685827 11 121482368 SORL1 SORL1 G/T 0.019 1.19 1.13–1.25 2.8 × 10−11 rs11218343 11 121564878 SORL1 SORL1 C/T 0.039 0.84 0.81–0.87 1.4 × 10−21 rs17125924 14 52924962 FERMT2 FERMT2 G/A 0.089 1.1 1.07–1.12 8.3 × 10−16 rs7401792 14 92464917 SLC24A4 SLC24A4/RIN3 G/A 0.371 1.04 1.02–1.05 4.8 × 10−8 rs12590654 14 92472511 SLC24A4 SLC24A4/RIN3 A/G 0.328 0.93 0.92–0.95 4.2 × 10−21 rs8025980 15 50701814 SPPL2A SPPL2A G/A 0.345 0.96 0.94–0.97 1.3 × 10−8 rs602602 15 58764824 MINDY2 ADAM10 A/T 0.28 0.94 0.93–0.96 2.1 × 10−15 rs117618017 15 63277703 APH1B APH1B T/C 0.144 1.11 1.09–1.13 2.2 × 10−25 rs889555 16 31111250 BCKDK KAT8 T/C 0.281 0.95 0.94–0.97 2.0 × 10−11 rs4985556 16 70660097 IL34 IL34 A/C 0.115 1.07 1.05–1.09 6.0 × 10−10 rs12446759 16 81739398 PLCG2 PLCG2 G/A 0.403 0.95 0.94–0.96 1.2 × 10−13 rs72824905 16 81908423 PLCG2 PLCG2 G/C 0.008 0.74 0.68–0.81 8.5 × 10−12 rs7225151 17 5233752 SCIMP SCIMP/RABEP1 A/G 0.124 1.08 1.05–1.10 4.1 × 10−13 rs199515 17 46779275 WNT3 MAPT G/C 0.219 0.94 0.93–0.96 9.3 × 10−13 rs616338 17 49219935 ABI3 ABI3 T/C 0.012 1.32 1.23–1.42 2.8 × 10−14 rs2526377 17 58332680 TSPOAP1 TSPOAP1 G/A 0.445 0.95 0.94–0.97 1.6 × 10−12 rs4277405 17 63471557 ACE ACE C/T 0.384 0.94 0.93–0.95 8.8 × 10−20 rs12151021 19 1050875 ABCA7 ABCA7 A/G 0.336 1.1 1.09–1.12 1.6 × 10−37 rs6014724 20 56423488 CASS4 CASS4 G/A 0.09 0.89 0.87–0.91 4.1 × 10−21 rs2830489 21 26775872 ADAMTS1 ADAMTS1 T/C 0.281 0.95 0.94–0.97 1.7 × 10−10 P values are two-sided raw P values derived from a fixed-effect meta-analysis.Ci, confidence interval; Or, odds ratio; MAF, minor allele frequency. areference single-nucleotide polymorphism (SNp) (rs) number, according to dbSNp build 153. bGrCh38 assembly. cNearest protein-coding gene according to GENCODE release 33. dWeighted average MAF across all discovery studies. eApproximate Or calculated with respect to the minor allele. NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 414 Articles NATure GeNeTiCs Table 2 | Summary of association results in the stage i and stage ii analysis for new loci at the time of analysis with a genome-wide significant signal Locus number Variantachromosome PositionbGenecMinor/major allele MAFdOre95% ci P value 1rs141749679 1 109345810 SORT1 C/T 0.004 1.38 1.24–1.54 7.5 × 10−9 2rs72777026 2 9558882 ADAM17 G/A 0.144 1.06 1.04–1.08 2.7 × 10−8 3rs17020490 2 37304796 PRKD3 C/T 0.145 1.06 1.04–1.08 3.3 × 10−9 4rs143080277 2 105749599 NCK2 C/T 0.005 1.47 1.33–1.63 2.1 × 10−13 5rs139643391 2 202878716 WDR12 T/TC 0.131 0.94 0.92–0.96 1.1 × 10−8 6rs16824536 3 155069722 MME A/G 0.054 0.92 0.89–0.95 3.6 × 10−8 6rs61762319 3 155084189 MME G/A 0.026 1.16 1.11–1.21 2.2 × 10−11 7rs3822030 4 993555 IDUA G/T 0.429 0.95 0.94–0.96 8.3 × 10−12 8rs2245466 4 40197226 RHOH G/C 0.343 1.05 1.03–1.06 1.2 × 10−9 9rs112403360 5 14724304 ANKH A/T 0.073 1.09 1.06–1.12 2.3 × 10−9 10 rs62374257 586927378 COX7C C/T 0.23 1.07 1.05–1.09 1.4 × 10−15 11 rs871269 5 151052827 TNIP1 T/C 0.326 0.96 0.95–0.97 8.7 × 10−9 12 rs113706587 5 180201150 RASGEF1C A/G 0.11 1.09 1.07–1.12 2.2 × 10−16 13 rs785129 6 114291731 HS3ST5 T/C 0.35 1.04 1.03–1.06 2.4 × 10−9 14 rs6943429 7 7817263 UMAD1 T/C 0.42 1.05 1.03–1.06 1.0 × 10−10 15 rs10952097 7 8204382 ICA1 T/C 0.114 1.07 1.05–1.10 6.8 × 10−9 16 rs13237518 7 12229967 TMEM106B A/C 0.411 0.96 0.94–0.97 4.9 × 10−11 17 rs1160871 7 28129126 JAZF1 G/GTCTT 0.222 0.95 0.93–0.97 9.8 × 10−9 18 rs76928645 7 54873635 SEC61G T/C 0.103 0.93 0.91–0.95 1.6 × 10−10 19 rs1065712 8 11844613 CTSB C/G 0.053 1.09 1.06–1.12 1.9 × 10−9 20 rs34173062 8 144103704 SHARPIN A/G 0.081 1.13 1.09–1.16 1.7 × 10−16 21 rs1800978 9 104903697 ABCA1 G/C 0.13 1.06 1.04–1.08 1.6 × 10−9 22 rs7068231 10 60025170 ANK3 T/G 0.403 0.95 0.94–0.96 3.3 × 10−13 23 rs6586028 10 80494228 TSPAN14 C/T 0.196 0.93 0.91–0.94 2.0 × 10−19 24 rs6584063 10 96266650 BLNK G/A 0.043 0.89 0.86–0.92 6.7 × 10−11 25 rs7908662 10 122413396 PLEKHA1 G/A 0.467 0.96 0.95–0.97 2.6 × 10−9 26 rs6489896 12 113281983 TPCN1 C/T 0.076 1.08 1.05–1.10 1.8 × 10−9 27 rs7157106 14 105761758 IGH gene cluster A/G 0.36 1.05 1.03–1.07 2.0 × 10−8 27 rs10131280 14 106665591 IGH gene cluster A/G 0.133 0.94 0.92–0.96 4.3 × 10−10 28 rs3848143 15 64131307 SNX1 G/A 0.22 1.05 1.04–1.07 8.4 × 10−11 29 rs12592898 15 78936857 CTSH A/G 0.133 0.94 0.92–0.96 4.2 × 10−9 30 rs1140239 16 30010081 DOC2A T/C 0.379 0.94 0.93–0.96 2.6 × 10−13 31 rs450674 16 79574511 MAF C/T 0.373 0.96 0.95–0.98 3.2 × 10−8 32 rs16941239 16 86420604 FOXF1 A/T 0.029 1.13 1.08–1.17 1.3 × 10−8 33 rs56407236 16 90103687 PRDM7 A/G 0.069 1.11 1.08–1.14 6.5 × 10−15 34 rs35048651 17 1728046 WDR81 T/TGAG 0.214 1.06 1.04–1.08 7.7 × 10−11 35 rs2242595 17 18156140 MYO15A A/G 0.112 0.94 0.92–0.96 1.1 × 10−9 36 rs5848 17 44352876 GRN T/C 0.289 1.07 1.06–1.09 2.4 × 10−20 37 rs149080927 19 1854254 KLF16 G/GC 0.48 1.05 1.04–1.07 5.1 × 10−10 38 rs9304690 19 49950060 SIGLEC11 T/C 0.24 1.05 1.03–1.07 4.7 × 10−9 39 rs587709 19 54267597 LILRB2 C/T 0.325 1.05 1.04–1.07 3.6 × 10−11 40 rs1358782 20 413334 RBCK1 A/G 0.246 0.95 0.94–0.97 1.6 × 10−8 41 rs6742 20 63743088 SLC2A4RG T/C 0.221 0.95 0.93–0.97 2.6 × 10−9 42 rs2154481 21 26101558 APP C/T 0.476 0.95 0.94–0.97 1.0 × 10−12 P values are two-sided raw P values derived from a fixed-effect meta-analysis. ars number, according to dbSNp build 153. bGrCh38 assembly. cNearest protein-coding gene according to GENCODE release 33. dWeighted average MAF across all discovery studies. eApproximate Or calculated with respect to the minor allele. NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 415 Articles NATure GeNeTiCs From all newly identified loci, this gene prioritization yielded 31 tier 1 genes and 24 tier 2. The 55 prioritized genes, the details of the analyses and the supporting evidence are summarized in Fig. 2a and the Supplementary Note (Supplementary Tables 19–30 and Supplementary Figs. 35–45). Among the 31 tier 1 genes, we observed that 25 of these genes were the only prioritized gene in their respective locus. For the remaining 6 tier 1 genes, we also found tier 2 genes in their respective locus. We also identified five loci containing several tier 2 prioritized genes. In one of these loci, locus 39 (L39), the tier 2 prioritized gene LILRB2 had strong additional support from published literature (Supplementary Note). In five loci, our prioritization score did not identify sufficient molecular evidence to prioritize genes with exception of being the nearest gene (L10, L12, L13, L14 and L32). Finally, we excluded the complex IGH cluster (L27) from gene prioritization analyses due to genomic complexity of the telomeric locus as a consequence of known fusion events18. We highlight two examples, L18 and L23. In L18, the lead variant, rs76928645 (MAF = 10%), is intergenic and is located more than 100 kb downstream or upstream of the two nearest protein-coding genes (SEC61G and EGFR, respectively). Our gene prioritization analyses suggested that EGFR was the only risk gene (Fig. 3). We found that both the lead variant (rs76928645) and the other nearby variants in linkage disequilibrium (LD) are significant expression QTLs (eQTLs) for regulating EGFR expression downstream. The eQTL signals in brain strongly colocalized with the GWAS signal (with eQTL coloc PP4s of 98.3% in the temporal cortex (TCX) and 99.5% in the dorsolateral prefrontal cortex (DLPFC)). Accordingly, the fine-mapped expression transcriptome-wide association study (eTWAS) associations (Fine-mapping Of CaUsal gene Sets (FOCUS) posterior inclusion probability (PIP) = 1; eTWAS P = 6.9 × 10−9, eTWAS Z = + 5.8 in the TCX; eTWAS P = 3.1 × 10−11, eTWAS Z = + 6.6 in the DLPFC) indicated that genetic downregulation of EGFR expression is associated with a lower ADD risk (Fig. 3; Supplementary Tables 22, 24 and 26; and Supplementary Figs. 36a, 39 and 41). In L23, we observed numerous eQTL-GWAS and methylation QTL (mQTL)-GWAS hits for TSPAN14 that support the hypothesis that increased brain expression of TSPAN14 is associated with increased ADD risk. We also identified several splice junctions in TSPAN14 whose genetic regulation signals in lymphoblastoid cell lines (LCLs) and brain colocalized with the ADD association signal. These splice junctions were also associated with ADD risk (Fig. 4, Supplementary Tables 22–28 and Supplementary Figs. 36–42 and 44c). As three of these splice junctions were related to new complex cryptic splicing events that were predicted to result in two cryptic exons not previously described in known TSPAN14 transcripts (based on GENCODE v38), we designed a long-read single-molecule (Nanopore) sequencing experiment (Supplementary Note) to validate these cryptic exons on a total of 93 complementary DNA (cDNA) samples derived from LCLs, frontal cortex and hippocampus and consequently validated those cryptic exons (Fig. 4). All three of the validated cryptic splicing events occur within the ADAM10-interacting domain of TSPAN14. Cryptic exon 1 is at least 45 bp long, and cryptic exon 2 is 118 bp long. Lastly, we used STRING v11 (ref. 19) to analyze protein–protein interaction for (1) previously known AD genes from GWASs, (2) our prioritized new genes (tier 1 in Fig. 2a and Supplementary Table 20) and (3) a combination of the two (Supplementary Note). The largest networks contained 14, 8 and 30 proteins, respectively (Supplementary Fig. 46). These networks were larger than would be expected by chance (respectively, P < 2 × 10−5, P = 2.8 × 10−3 and P < 2 × 10−5 based on comparison with 50,000 randomly simulated protein lists matched for the number of proteins and the total number of interactions for each protein). Notably, the number of interactions between our prioritized genes and previously known genes is also significantly greater than would be expected (P < 1 × 10−4), indicating that the newly prioritized genes are biologically relevant in AD. No such enrichment (P = 0.88) was observed for the remaining genes in the new loci, again highlighting the value of our prioritization approach. We next performed a pathway enrichment analysis of the tier 1 genes using STRING. We found that several gene sets linked to the immune system remained statistically significant after correction for multiple testing (Fig. 2b and Supplementary Table 31), especially regulation of the tumor necrosis factor (TNF)-mediated signaling pathway (GO:0010803). We report the potential genetic implication of the linear ubiquitin chain assembly complex (LUBAC), which is a major regulator of the aforementioned signaling pathway20. Two of the LUBAC’s three complements are encoded by the new tier 1 prioritized genes SHARPIN and RBCK1, and the complex’s function is directly regulated by OTULIN (also a new tier 1 prioritized gene). GrS We next looked at whether the genetic ADD burden (as measured by a genetic risk score (GRS)) generated from our genome-wide significant variants (n = 83, excluding APOE; Supplementary Table 32) might influence the rate of conversion to AD in (1) individuals from several prospective, population-based cohorts and (2) patients with mild cognitive impairment (MCI) in prospective memory clinic studies (Supplementary Table 33). We used Cox regression models to assess the association after adjustment for age at baseline, sex, the number of APOE-ε4 and APOE-ε2 alleles, and genetic principal components (PCs). In population-based cohorts with clinically diagnosed AD cases, the GRS was significantly associated with conversion to AD; this was shown in a fixed-effect meta-analysis (hazard ratio (HR) (95%CI) per average risk allele = 1.076 (1.064–1.088), P = 9.2 × 10−40; Fig. 5 and Supplementary Table 34). Likewise, the GRS was significantly associated with AD conversion in patients with MCI (HR = 1.056 (1.040–1.072), P = 2.8 × 10−12; Fig. 5 and Supplementary Table 35). Furthermore, we found that the GRS association increased significantly when the new variants discovered in the present study were added to the previously described variants (Supplementary Table 36) for both population-based studies (HR = 1.052 (1.037– 1.068), P = 1.5 × 10−11) and MCI cohorts (HR = 1.034 (1.013–1.055), P = 1.4 × 10−3). Fig. 2 | Gene prioritization. a, Summary of weighted scores for each evidence category for the prioritized genes in the 42 new genome-wide-significant loci. Using our gene prioritization method, we considered the genes within 1 Mb of each new lead variant and prioritized a total of 55 genes in 42 new loci at two different confidence levels (31 tier 1 genes and 24 tier 2 genes). The leftmost squares indicate the new locus index number. The different types of evidence are colored according to the seven different domains to which they belonged. Weighted scores for each evidence category are rescaled to a 0–100 scale, and the proportions of mean human brain cell-type-specific expression for each gene are also rescaled to a 0–100 scale; darker colors represent higher scores or higher expression proportions. Tier 1 genes are shown in dark green, and tier 2 genes are shown in light green. Only tier 1 and tier 2 genes are shown for each locus. Supplementary Fig. 35 shows full results. MAFs and CADD (v1.6) pHrED scores for rare and/or protein-altering rare variants are labeled in white within the respective squares. b, pathway enrichment analysis based on the tier 1 gene list. Only the ten strongest associations (according to STriNG software) are presented here. coloc, colocalization; eQTL, expression QTL; eTWAS, expression transcriptome-wide association study; GO, Gene Ontology; haQTL, histone acetylation QTL; Mon. Mac., monocytes and macrophages; sTWAS, splicing transcriptome-wide association study; m/haQTL, methylation/histone acetylation QTL; sQTL, splicing QTL; FDr, false discovery rate. NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 416 Articles NATure GeNeTiCs 0.5% 22.8 0.5% 23.1 19 10 16.4 44.4 100 100 66.7 66.7 81.8100 88.9 100 100 100 100 100 44.4 33.3 100 50 100 100 66.7 33.3 66.7 88.9 33.3 66.7 66.7 33.3 100 100 100 66.7 44.4 50 100 66.7 66.7 100 100 100 100 66.7 88.9 72.766.7 50 33.3 100 66.7 100 77.8 66.7 44.4 100 50 100100 100 100 100 10066.7 77.8 100 100 100 100 33.3 100 33.3 50 50 33.3 33.3 66.7 100 44.4 33.3 33.3 50 33.3 100 100 66.7 66.7 100 55.6 44.4 44.4 100 100 44.4 33.3 100 77.8 66.7 100 100 50 100 100 50 50 66.7 100 75 100 75 100 100 75 66.7 100 75 66.7 66.7 66.7 100 66.7 66.7 100 100 66.7 100 66.7 66.7 66.7 100 100 40 40 75 40 100 100 40 100 40 100 100 66.7 75 40 66.7 50 40 100 100 100 100 100 100 100 100 1 2 1 2 2 2 1 1 1 1 2 1 1 2 1 2 2 2 1 1 1 1 1 1 1 1 2 1 1 1 1 2 2 2 1 1 1 2 2 2 1 2 1 2 2 1 2 2 2 1 2 2 1 1 1 7.2 22.767.2 1145.9 11 10.6 21.4 15.9 19.7 14 23.2 17.4 8.3 24.3 16.3 17.7 13.3 13 10.8 32.5 23 30.5 14.1 14.3 9.5 11.7 11.2 11.5 20.5 23.5 30 7.9 15 7.8 12.2 5.77.611.5 59.33.7 21.7 6.924.134.3 3.99.1 7.3 1.349.221.7 15.74.8 17.2 24.8 22.5 28.6 18.5 7.3 15.1 9.9 18.4 21.9 8.4 7.4 1.4 2.90.60.8 92.61.7 10.3 31.97.36.3 28.515.7 20.4 18.522.817.3 129 9.8 30.68.37.4 31.512.5 0.4 01.12 94.42 9.2 020.29.9 3.557.2 14.8 9.417.615.4 27.615.2 1.3 30.42628.7 12.31.4 10.6 12.62818.5 10.420 4 10.513.814.6 45.112 34.8 4122.80.6 0.20.5 4.5 20.210.48.4 51.84.6 18.8 12.89.46.3 35.717 46 1410.33.6 188.1 19.7 1 7.8 0.7 15.9 22.2 22.9 21.6 24.2 2.4 9.5 52 6.2 50.33.54.9 30.94.2 0.9 0.10.40.4 97.60.7 4.2 16.217.122.4 10.229.9 14.8 40.4 31 0.9 18.7 12.5 20.9 13.2 1.7 18.6 12.8 14.4 7.3 9.9 15 12.3 13.3 8 9.4 8.3 36.7 22.7 18.3 38.9 34.6 19.92.41.7 40.41 17.8 10.11634.3 16.35.6 4.1 0.633.20.7 56.15.2 1 98.60.10.1 0.30 27.7 36.2 8.5 9.3 17.8 11.1 20.1 8.5 14.3 21 11.6 14 18 9.4 10.8 1.3 8.8 7.7 6.9 5.5 42.3 63.8 13.3 12.3 8.5 23.2 15.7 17.3 4.6 19.4 28.6 6 20.8 33.3 5.3 16.8 6.5 7.4 14.8 5.8 53.6 12.5 5.1 39.33.92.9 40.38.4 16.2 20.2 8.6 6.9 19.8 11 18.2 9.1 8.6 9.5 9.7 9.2 26.4 24.6 58 22.8 16.5 4.6 0.2 0.10.20.3 98.60.6 3.3 0 0.2 0.1 18.5 0 17.9 0 18.7 99.7 41.4 0.1 28 24.79.97.4 16.713.4 33.1 4.916.114 7.824.1 3.2 29.617.216.1 2.731.1 Variant annotation AD−relevant brain regions (AMP-AD and GTEx) Blood Microglia (MiGA) Mon. Mac. LCL (EADB Belgian and GTEx) APP Tier Single-cell expression (Allen Brain Atlas) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 Rare Nearest Protein altering PWAS & pQTL coloc (Wingo et al. 85 ) Lead variant eQTL eQTL coloc and eTWAS Lead variant sQTL sQTL coloc and sTWAS Lead variant m/haQTL MetaMeth Lead variant eQTL eQTL coloc Lead variant sQTL sQTL coloc Lead variant eQTL Lead variant eQTL eQTL coloc and eTWAS Lead variant sQTL sQTL coloc and sTWAS APP metabolism Gene prioritization Astrocytes Endothelial cells GABAergic neurons Glutamatergic neurons Microglia Oligodendrocytes SORT1 ADAM17 ITGB1BP1 PRKD3 CEBPZOS EIF2AK2 NCK2 ICA1L MME IDUA DGKQ RHOH OTULIN COX7C TNIP1 RASGEF1C HS3ST5 UMAD1 ICA1 TMEM106B JAZF1 EGFR CTSB SHARPIN ABCA1 ANK3 CCDC6 TSPAN14 BLNK PLEKHA1 IQCD RITA1 SNX1 FAM96A CTSH DOC2A MAF FOXF1 PRDM7 CDK10 SERPINF2 WDR81 TOP3A LLGL1 MYO15A GRN KLF16 REXO1 ATP8B3 SIGLEC11 LILRB2 MYADM RBCK1 LIME1 APP Category Prioritized gene 0 25 50 75 100 Per category rescaled score or per gene cell-type expression (%) Domain or type Variant annotation eQTL-GWAS integration sQTL-GWAS integration pQTL-GWAS integration mQTL-GWAS integration haQTL-GWAS integration APP metabolism Prioritized gene tier Single-cell expression GO term Term description Number of tier 1 genes Number of genes in pathway Matching proteins in the networkFDR GO:0001775 4.09 × 10 –5 1,024 GRN,CTSH, BLNK, NCK2, DGKQ, EGFR, APP, ADAM17, CTSB, RHOH, TSPAN14, MME GO:0002376 2.60 × 10 –4 2,370 GRN,CTSH, BLNK, NCK2, OTULIN, APP, LIME1, ADAM17, TNIP1, CTSB, RBCK1, PLEKHA1, RHOH, TSPAN14, MME GO:0009966 GRN,CTSH, BLNK, NCK2, DGKQ, EGFR, OTULIN, APP, ADAM17, TNIP1, RBCK1, PLEKHA1, ABCA1, RHOH, SHARPIN, TSPAN14, RITA1 GO:0010646 GRN,CTSH, BLNK, NCK2, DGKQ, EGFR, OTULIN, APP, ADAM17, TNIP1, RBCK1, PLEKHA1, ABCA1, RHOH, ICA1, SHARPIN, TSPAN14, RITA1 GO:0023051 2.60 × 10 –4 3,360 GRN,CTSH, BLNK, NCK2, DGKQ, EGFR, OTULIN, APP, ADAM17, TNIP1, RBCK1, PLEKHA1, ABCA1, RHOH, ICA1, SHARPIN, TSPAN14, RITA1 GO:0045321 2.60 × 10 –4 894 GRN, CTSH, BLNK, NCK2, APP, ADAM17, CTSB, RHOH, TSPAN14, MME GO:0048583 GRN,CTSH, BLNK, NCK2, DGKQ, EGFR, OTULIN, APP, LIME1, ADAM17, TNIP1, RBCK1, PLEKHA1, ABCA1, RHOH, SHARPIN, TSPAN14, SIGLEC11, RITA1 GO:0048584 CTSH, BLNK, NCK2, EGFR, OTULIN, APP, LIME1, ADAM17, TNIP1, RBCK1, PLEKHA1, SHARPIN, TSPAN14 GO:0010803 OTULIN, ADAM17, RBCK1, SHARPIN GO:0042058 12 15 17 3,033 2.60 × 10 –4 18 3,327 2.60 × 10 –4 18 10 19 3,882 2.60 × 10 –4 14 2,054 2.60 × 10 –4 4 56 4.30 × 10 –4 4 80 1.50 × 10 –3 NCK2, EGFR, APP, ADAM17 b a Cell activation Immune system process Regulation of signal transduction Regulation of cell communication Regulation of signaling Leukocyte activation Regulation of response to stimulus Positive regulation of response to stimulus Regulation of TNF-mediated signaling pathway Regulation of EGFR signaling pathway NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 417 Articles NATure GeNeTiCs Importantly, the results of our meta-analysis suggest that the risk of conversion to AD rises with the number of risk alleles from non-APOE risk variants in the GRS by 1.9-fold in population-based cohorts (HR = 1.93 (1.75–2.13); Fig. 5) and 1.6-fold in MCI cohorts (HR = 1.63 (1.42–1.87); Fig. 6) on top of effects of age and the APOE ε4 allele. These observations result from the comparison of hypothetical individuals with a GRS value at the first decile of the distribution versus those with a GRS value at the ninth decile (Fig. 6). With regard to APOE, carrying an additional APOE-ε4 allele was associated with a slightly higher increase in the AD risk in population-based cohorts (HR = 2.19 (2.03–2.37)) and MCI cohorts (HR = 1.90 (1.73–2.07)). There was no interaction between the GRS and the number of APOE-ε4 alleles (Supplementary Table 37). In an MCI cohort setting, this effect of the GRS corresponds to a median AD conversion probability within 3 years of 21.9% in patients with a GRS below the first decile (range, 4.1–34.9%) and 37.5% (range, 10.8–56.2%) in patients with a GRS above the ninth decile. There was a consistent increase in probability between these deciles in all cohorts (median (range), 13.8% (6.6–25.0%); Supplementary Table 38). To better define the GRS discriminative ability regarding AD conversion, we assessed the improvements in three indices of predictive performance after adding the GRS to a Cox model containing age, sex, PCs and the number of APOE-ε4 and APOE-ε2 alleles as covariates (Supplementary Tables 34 and 35). We found a small but consistent increase in the discrimination between AD converters and nonconverters, as indicated by the concordance index (C-index) in SEC61G locus (18) eQTL-GWAS regional plot 17.5 15 10 5 0 2 0 –2 0 2.5 5.0 7.5 rs76928645 eQTL-EGFR MayoRNAseq TCX rs76928645 genotype CC CT TT EGFR 0.8 0.6 0.4 0.2 r2 a b c 15.0 12.5 10.0 7.5 5.0 2.5 SEC61G EGFR LOC100996654 GWAS or eQTL –log10 (P) 0 17.5 15.0 12.5 10.0 7.5 5.0 2.5 0 17.5 15.0 12.5 10.0 7.5 5.0 2.5 0 EADB GWAS stage I rs76928645 rs76928645 rs76928645 SEC61G eQTL-MayoRNAseq TCX EGFR eQTL-MayoRNAseq TCX 54.7 Mb 54.8 Mb 54.9 Mb Chromosome 7 55 Mb 54.7 Mb 54.8 Mb 54.9 Mb Chromosome 7 55 Mb 54.7 Mb 54.8 Mb 54.9 Mb Chromosome 7 55 Mb PP4: 98.3% eTWAS Z: +5.8 eQTL P: 3 × 10–18 Z: +5.8 eQTL β : –0.39 MayoRNAseq TCX sQTL –log10(P) Normalized EGFR expression EADB GWAS –log10(P) Fig. 3 | regulation of eGFr expression by the ADD-risk-associated and colocalized brain eQtLs within the intergenic Sec61G locus. a, The regional plot of the new SEC61G locus (L18) shows the EADB GWAS stage i (n = 487,511) ADD association signal within 200 kb of the intergenic lead variant, rs76928645 (the two closest protein-coding genes, SEC61G and EGFR, are more than 100 kb from the lead variant), together with the eQTLs in the same region identified for SEC61G and EGFR expression separately in the TCX (MayorNAseq TCX eQTL catalog based on n = 259 individuals). The rs7692864 lead variant is shown in purple, and LD r2 values (calculated for the EADB Trans-Omics for precision Medicine (TOpMed) dataset (n = 42,140) with respect to the lead variant) are indicated on a color scale. y axis, −log10 for the GWAS or eQTL P value; x axis, hg38 genomic position on chromosome 7. b, Colocalization between the EGFR eQTL signal (MayorNAseq TCX, n = 259 individuals) and the EADB GWAS stage i (n = 487,511) signal (eQTL coloc pp4 = 98.3%); with the significant eTWAS association (eTWAS P = 6.9 × 10−9 and eTWAS Z = 5.8) and fine-mapped (FOCUS pip = 1) eTWAS association in the same catalog. y axis, eQTL −log10(P) value; x axis, GWAS −log10(P) value. LD r2 values and color scales are as in a. c, The eQTL violin plot shows a significant association (eQTL P = 3 × 10−18) between the rs76928645 lead variant genotype and EGFR expression in the TCX (MayorNAseq TCX, n = 259 individuals), where the protective allele T is associated with lower EGFr expression (eQTL β, −0.39). Each data point represents a sample whose normalized EGFR expression value is indicated on the y axis, and the rs76928645 genotype information is indicated on the x axis. The lower and upper hinges of the boxes represent the first and third quantiles, the whiskers extend 1.5 times the interquartile range from the hinges and the line represents the median. NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 418 Articles NATure GeNeTiCs population-based cohorts (Δ5years-C-indexfixed-effects = 0.002 (0.0004– 0.004)) and MCI cohorts (Δ3years-C-indexfixed-effects = 0.007 (0.001– 0.012)). This finding was further supported by small-to-moderate increases in the continuous NRI (net reclassification improvement) index in population-based cohorts (NRI5year-fixed-effects = 0.248 (0.159– 0.336)) and MCI cohorts (NRI3year-fixed-effects = 0.232 (0.140–0.325)); this indicates that the risk assignment is more appropriate to individuals when the GRS is taken into account21. Furthermore, an increase in the index of prediction accuracy (IPA) was observed in all of the population-based cohorts (average Δ5years-IPAfixed-effects = 0. 29% (0.23%–0.35%)) and all but one of the MCI cohorts (average Δ3years-IPAfixed-effects = 1.53% (1.31%–1.76%)), indicating an overall improvement in predictive performance. As expected, the amount of improvement in this index varied greatly from one cohort to another, given its dependency on incidence rates. The value of adding the new genetic variants was emphasized by the fact that effect sizes (as measured by the indices of predictive ability) were lower when only previously known AD risk variants were included in the GRS (Supplementary Table 39). The results were similar when we (1) computed indices for other follow-up time points, (2) applied a random effects meta-analysis, (3) considered conversion to all-cause-dementia as the outcome and (4) excluded the Framingham Heart Study (FHS), as it was part of the stage II of the GWAS from which ORs for PRS computation were extracted (Supplementary Tables 34–44 and Supplementary Fig. 47). Discussion Our meta-analysis combined a large, new case–control study with previous GWASs. We identified 75 independent loci for ADD; 33 had been reported previously, and 42 correspond to new signals at the time of this analysis. The prioritized genes and their potential impact on the pathophysiology of AD are described in the Supplementary Note. Our pathway enrichment analyses removed ambiguities concerning the involvement of tau-binding proteins and APP/Aβ peptide metabolism in late-onset AD processes at a much higher level than had been described previously5. It is noteworthy that new genetic risk factors are often first evaluated in the context of known pathways; many new research approaches were developed to systematically characterize putative links among APP metabolism, tau function and ADD genetic risk factors22,23. This approach can lead to circular reasoning and thus artificial enrichment in specific processes. However, we implicate ADAM17, a gene whose protein product is known to carry α-secretase activity as ADAM10 (ref. 24). This observation suggests that the nonamyloidogenic pathway for APP metabolism might be deregulated in AD. In addition to APP, we also identified six highly plausible prioritized (tier 1) genes (ICA1L, DGKQ, ICA1, DOC2A, WDR81 and LIME1) that are likely to modulate the metabolism of APP. These pathway enrichment analyses also confirmed the involvement of innate immunity and microglial activation in ADD (Supplementary Table 15). Our single-cell expression enrichment analysis also highlighted genes expressed in microglia (Supplementary Tables 16 and 17). Indeed, three of our prioritized (tier 1) genes (RHOH, BLNK and SIGLEC11) and two of our tier 2 genes (LILRB2 and RASGE1FC) appeared to be mainly expressed in microglia (>90% relative to the total expression summed across cell types; Fig. 2a and Supplementary Table 45). Importantly, SIGLEC11 and LILRB2 have already been linked to Aβ peptides/amyloid plaques25,26. Here, we also provide genetic evidence of the LUBAC’s potential implication in ADD. Two of the LUBAC’s three complements are encoded by SHARPIN and RBCK1, and the LUBAC is regulated by OTULIN; all three genes were found to be high-confidence, prioritized risk genes in our study. The LUBAC is the only E3 ligase known to form linear ubiquitin chains de novo through ubiquitin’s N-terminal methionine. The complex has mostly been studied in the context of inflammation, innate immunity and defense against intracellular pathogens. For instance, the LUBAC is reportedly essential for NLRP3 inflammasome activation27 and thus acts as a key innate immune regulator28. In turn, the NLRP3 inflammasome is essential for the development and progression of Aβ pathology in mice29 and may drive tau pathology through Aβ-induced microglial activation30. The LUBAC is also reportedly involved in autophagy, and linear ubiquitin chain modifications of TDP-43-positive neuronal cytoplasmic inclusions have been described as potential inducers of autophagic clearance31. Lastly, the LUBAC has been studied as a regulator of TNF-α signaling in particular20. Interestingly, the TNF-α signaling pathway was also flagged by other genetic findings in our study (Supplementary Fig. 48). For example, ADAM17 (also known as TNF-α-converting enzyme) is of pivotal importance in the activation of TNF-α signaling32. For TNIP1, its gene product (TNF-α-induced protein 3-interacting protein 1) is involved in the inhibition of the TNF-α signaling pathway and nuclear factor κB activation/translocation33. Additional signal related to TNF-α is the one found at SPPL2A (one of the 33 confirmed loci). The protein encoded by SPPL2A is involved in noncanonical shedding of TNF-α34, and PGRN has been described as a TNF receptor ligand and an antagonist of TNF-α signaling35. Several lines of evidence had linked the inhibition of TNF-α signaling with reduction of both Aβ and tau pathologies in vivo36,37. Although a potential inflammatory connection has been suggested for TNF-α through the activation of NLRP3 inflammasome38, the TNF-α signaling pathway is also involved in many other brain physiological functions (e.g., synaptic plasticity in neurons) and pathophysiological processes (e.g., synapse loss) in the brain39. Furthermore, the involvement of the TNF-α signaling pathway and the LUBAC might be important in cell types other than microglia in AD. It is important Fig. 4 | Focus on TSPAN14 locus. a, Splicing QTL (sQTL)-GWAS integration results. Known TSPAN14 transcripts (GENCODE v38; green, coding sequences; gray, noncoding) plotted with −log10(P) for (1) EADB GWAS stage i (n = 487,511) signal (black), (2) sQTL signal for chr10:80509471–80510106 junction (supporting cryptic exon 1) in the EADB Belgian LCL sQTL catalog (n = 70 individuals, blue) and (3) sQTL signal for chr10:80512269–80512719 junction in the MayorNAseq TCX sQTL catalog (n = 259 individuals, red); hg38 genomic position is shown above. LCL and brain-based sQTL coloc and sTWAS analyses associate ADD risk with these junctions that suggest cryptic splicing within ADAM10-interacting domain of TSPAN14 (magenta), which was predicted to result in two cryptic exons. b, Long-read sequencing validation of TSPAN14 cryptic exons. Nanopore sequencing results (Supplementary Note) in the zoomed-in region of chr10:80506973–80516400 (cumulative coverage in log10 scale). pooled LCL cDNA sample sequenced for cDNA Amplicon2 shown in blue. cDNA Amplicon1 was sequenced on biologically independent hippocampal (HpC; n = 16, red), frontal cortex (FC; n = 18, pink) and LCL (n = 59, orange) cDNA samples. Green, canonical exons (8–12); dotted black lines, canonical splicing; blue, cryptic exon 1 (>45 bp); red, cryptic exon 2 (118 bp). All annotated junctions use canonical splice donor (GT) and acceptor (AG) sites. c,d, sQTL-GWAS colocalization plots for chr10:80509471– 80510106 (supporting cryptic exon 1) in the EADB Belgian LCL sQTL catalog (n = 70 individuals) (c) and chr10:80512269–80512719 (supporting cryptic exon 2) in the MayorNAseq TCX sQTL catalog (n = 259 individuals) (d). sQTL signals for the two junctions colocalize with ADD signal (pp4s of 98.8% and 97.4%, respectively), and sTWAS associates with increased preference for the cryptic splicing with decreased ADD risk (sTWAS P = 6.28 × 10−12 and 1.6 × 10−13, sTWAS Z = −6.9 and −7.4, respectively). y axis, sQTL −log10(P); x axis, EADB GWAS stage i −log10(P). LD r2 values calculated within EADB-TOpMed dataset (n = 42,140) based on the lead variant rs6586028 (purple) are indicated on a color scale. NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 419 Articles NATure GeNeTiCs to note that six of our prioritized (tier 1) genes (ICA1L, EGFR, RITA1, MYO15A, LIME1 and APP) are expressed at a low level in microglia (<10%, relative to the total expression summed across cell types; Supplementary Table 45), emphasizing that ADD results from complex crosstalk between different cell types in the brain23,40. It is also noteworthy that the EGFR pathway is known to interact with the TNF-α signaling pathway41, which suggests interplay between the two signaling pathways during the ADD development. A better understanding of the etiology of ADD might also result from the observation that the risks of developing ADD and frontotemporal dementia are associated with the same causal variants in GRN and TMEM106B. This association might be due to the misclassification of clinical diagnosis of AD and the presence of proxy-ADD cases in the UKBB. However, GRN and TMEM106B have also been linked to brain health and many other neurodegenerative diseases. For instance, GRN and TMEM106B are reportedly potential genetic GWAS signal Cryptic splicing (sQTL coloc and sTWAS hits) ADAM10-interacting domain cDNA amplicon1 Nanopore sequencing amplicons LCL amplicon2 Nanopore sequencing HPC amplicon1 Nanopore sequencing FC amplicon1 Nanopore sequencing LCL amplicon1 Nanopore sequencing Canonical splicing Cryptic splicing Exon 12 AG AGAG AGAG GT GT GTGT GT Exon 11Exon 10Exon 9 Chr10:80509471–80510106 Chr10:80512269–80512719 Cryptic exon 1 (>45 bp) Cryptic exon 2 (118 bp) Exon 8 0 15 10 5 0 15 10 5 0 5 EADB GWAS –log10(P) EADB Belgian LCL sQTL –log10(P) MayoRNAseq TCX sQTL –log10(P) EADB GWAS –log10(P) 10 0 5 10 cDNA amplicon2 80,530 Kb 80,516 Kb 80,52080,510 80,51480,51280,51080,508 80,50080,490 Chr10 Chr10 80,48080,47080,460 19 a b c d 19 –log10(P) 0 0 19 0 0 2.5 0 4.8 5.3 0 0 4.8 Cumulative coverage in log10 scale sQTL signal for cryptic exon 1 sQTL signal for cryptic exon 2 Known TSPAN14 transcripts (GENCODE v38) PP4: 98.8% sTWAS Z: –6.9 PP4: 97.4% sTWAS Z: –7.4 NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 420 Articles NATure GeNeTiCs Clinical Neurochemistry, Section of Neurology, University of perugia, perugia, italy. 124University of Milan, Milan, italy. 125Laboratory of Neurogenetics, Department of internal Medicine, Texas Tech University Health Science Center, Lubbock, TX, USA. 126reta Lila Weston research Laboratories, Department of Molecular Neuroscience, UCL institute of Neurology, London, UK. 127Faculty of Medicine, University of Lisbon, Lisbon, portugal. 128Department of psychiatry, Social Medicine Center East- Donauspital, Vienna, Austria. 129institute of Clinical Medicine, University of Oslo, Oslo, Norway. 130Glenn Biggs institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA. 131Dementia research Centre, UCL Queen Square institute of Neurology, London, UK. 132Unidad de Demencias, Servicio de Neurología y Neurofisiología. instituto de Biomedicina de Sevilla (iBiS), Hospital Universitario Virgen del rocío/CSiC/Universidad de Sevilla, Seville, Spain. 133instituto de investigacion Sanitaria ‘Hospital la paz’ (idipaz), Madrid, Spain. 134Centro de Biología Molecular Severo Ochoa (UAM-CSiC), Madrid, Spain. 135Hospital Universitario la paz, Madrid, Spain. 136Department of Geriatric psychiatry, Central institute for Mental Health, Mannheim, University of Heidelberg, Heidelberg, Germany. 137Department of Genetics and Genomic Sciences, ronald M. Loeb Center for Alzheimer’s Disease icahn School of Medicine at Mount Sinai, New York, NY, USA. 138Alzheimer research Center & Memory Clinic, Andalusian institute for Neuroscience, Málaga, Spain. 139Hospital Universitario ramon y Cajal, irYCiS, Madrid, Spain. 140Department of psychiatry and psychotherapy, Medical University of Vienna, Vienna, Austria. 141Department of Biostatistics, Epidemiology, and informatics perelman School of Medicine, University of pennsylvania, philadelphia, pA, USA. 142CAEBi, Centro Andaluz de Estudios Bioinformáticos, Sevilla, Spain. 143Center for Alzheimer research, Department NVS, Division of Neurogeriatrics, Karolinska institutet, Stockholm, Sweden. 144Unit for Hereditary Dementias, Karolinska University Hospital-Solna, Stockholm, Sweden. 145Aging research Center, Department of Neurobiology, Care Sciences and Society, Karolinska institutet and Stockholm University, Stockholm, Sweden. 146institute of public Health, University of Cambridge, Cambridge, UK. 147Department of Child and Adolescent psychiatry and psychotherapy, University Hospital of psychiatry Zurich, University of Zurich, Zurich, Switzerland. 148Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland. 149Zurich Center for integrative Human physiology, University of Zurich, Zurich, Switzerland. 150icelandic Heart Association, Faculty of Medicine, University of iceland, reykjavik, iceland. 151Human Genetics, School of Life Sciences, Life Sciences Building, University park, University of Nottingham, Nottingham, UK. 152Ai Virtanen institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland. 153Department of Neurology, Medical School, University of Cyprus, Nicosia, Cyprus. 154The John p. Hussman institute for Human Genomics, University of Miami, Miami, FL, USA. 155GrC 21, Alzheimer precision Medicine initiative (ApMi), Sorbonne University, Ap-Hp, pitié-Salpêtrière Hospital, paris, France. 156institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany. 157institute of Clinical Medicine, Neurology, University of Eastern, Kuopio, Finland. 158institute of Clinical Medicine, internal Medicine, University of Eastern Finland, Kuopio, Finland. 159Clinical and Experimental Science, Faculty of Medicine, University of Southampton, Southampton, UK. 160Nash Family Department of Neuroscience & Friedman Brain institute, icahn School of Medicine at Mount Sinai, New York, NY, USA. 161Department of Neurology, UMC Utrecht Brain Center, Utrecht, the Netherlands. 162Biostatistics, University of Kentucky College of public Health, Lexington, KY, USA. 163Department of Biology, Brigham Young University, provo, UT, USA. 164Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK. 165Division of Clinical Geriatrics, Center for Alzheimer research, Care Sciences and Society (NVS), Karolinska institutet, Stockholm, Sweden. 166institute of public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland. 167Neuroepidemiology and Ageing research Unit, School of public Health, imperial College London, London, UK. 168research & Development, UnitStockholms Sjukhem, Stockholm, Sweden. 169Department of Neurology, Kuopio University Hospital, Kuopio, Finland. 170Department of Neurosciences, University of Helsinki and Department of Geriatrics, Helsinki University Hospital, Helsinki, Finland. 171Department of psychiatry and psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany. 172Laboratory of Cognitive Neuroscience, School of psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece. 173Department of Epidemiology, University of Washington, Seattle, WA, USA. 174Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and iDiVAL), Santander, Spain. 175Stockholm Gerontology research Center, Stockholm, Sweden. 176Laboratory of Epidemiology, Demography, and Biometry, National institute of Aging, The National institutes of Health, Bethesda, MD, USA. 177intramural research program/National institute on Aging/National institutes of Health, Bethesda, MD, USA. 178public Health promotion Unit, Finnish institute for Health and Welfare, Helsinki, Finland. 179Memory Clinic, Department of Neurology, Charles University, 2nd Faculty of Medicine and Motol University Hospital, praha, Czechia. 180international Clinical research Center, St. Anne’s University Hospital Brno, Brno, Czechia. 181Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, USA. 182Department of Neurology, Hospital Universitario Donostia, OSAKiDETZA-Servicio Vasco de Salud, San Sebastian, Spain. 183Department of Neurology, Columbia University, New York, NY, USA. 184School of Health Sciences, Bangor University, Bangor, UK. 185institute of Neurology, Catholic University of the Sacred Heart, rome, italy. 186Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA. 187MrC prion Unit at UCL, UCL institute of prion Diseases, London, UK. 188Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología. instituto de Biomedicina de Sevilla (iBiS), Hospital Universitario Virgen del rocío/CSiC/Universidad de Sevilla, Seville, Spain. 189institute for Urban public Health, University Hospital of University Duisburg-Essen, Essen, Germany. 190Neurological Tissue Bank of the Biobanc-Hospital Clinic-iDiBApS, institut d’investigacions Biomèdiques August pi i Sunyer, Barcelona, Spain. 191Alzheimer’s Disease and Other Cognitive Disorders Unit, Neurology Department, Hospital Clinic, Barcelona, Spain. 192Laboratory of Brain Aging and Neurodegeneration, FiL-CONiCET, Buenos Aires, Argentina. 193Human Genetics, School of Life Sciences, University of Nottingham, Nottingham, UK. 194Memory impairment and Neurodegenerative Dementia (MiND) Center, University of Mississippi Medical Center, Jackson, MS, USA. 195Laboratorio de Bioquímica Molecular, Facultad de Medicina, instituto de investigaciones Médicas A. Lanari, UBA, C.A.B.A, Buenos Aires, Argentina. 196Department of Medicine, University of Washington, Seattle, WA, USA. 197irCCS Fondazione Don Carlo Gnocchi, Florence, italy. 198Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark. 199DiMEC, University of parma, parma, italy. 200resources and research Memory Center (MrrC) of Distalz, LicendUniversity of Lille, iNSErM, CHU Lille, UMr1172, Lille, France. 201institut de Biomedicina de València-CSiC CiBErNED, València, Spain. 202Unitat Mixta de de Neurología y Genética, institut d’investigació Sanitària La Fe, València, Spain. 203US 41-UMS 2014-pLBS, bilille, Université de Lille, CNrS, iNSErM, CHU Lille, institut pasteur de Lille, Lille, France. 204institute of psychiatry and psychotherapy, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin institute of Health, Berlin, Germany. 205German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany. 206Department of Biomedical Sciences, University of Cagliari, Cagliari, italy. 207CHUV, Old Age psychiatry, Department of psychiatry, Lausanne, Switzerland. 208Old Age psychiatry, Department of psychiatry, Lausanne University Hospital, Lausanne, Switzerland. 209Department of Geriatric psychiatry, University Hospital of psychiatry Zürich, Zürich, Switzerland. 210Department of Neuropsychiatry and Laboratory of Molecular psychiatry, Charité, Charitéplatz 1, Berlin, Germany. 211Department of Clinical Biochemistry, rigshospitalet, Copenhagen, Denmark. 212Department of psychiatry & Neuropsychologie, Maastricht University, Alzheimer Center Limburg, Maastricht, the Netherlands. 213Depatamento de Especialidades Quirúrgicas Bioquímica e inmunología, Facultad de Medicina, Universidad de Málaga, Málaga, Spain. 214Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands. 215Taub institute, Columbia University, New York, NY, USA. 216Bioinformatics, College of Life Sciences, Brigham Young University, provo, UT, USA. 217institute of Social Medicine, Occupational Health and public Health, University of Leipzig, Leipzig, Germany. 218Center of Mental Health, Clinic and policlinic of psychiatry, psychosomatics and psychotherapy, University Hospital of Würzburg, Wuerzburg, Germany. 219Department of research and innovation, Helse Fonna, Haugesund Hospital, Haugesund, Norway. 220institute of Clinical Medicine (K1), The University of Bergen, Bergen, Norway. 221Departamento de Especialidades Quirúrgicas, Bioquímicas e inmunología, School of Medicine, University of Málaga, Málaga, Spain. 222Department of Neuroscience and Mental Health, AOU Città della Salute e della Scienza di Torino, Torino, italy. 223Athens Association of Alzheimer’s Disease and related Disorders, Athens, Greece. 224Department of Geriatrics, St. Olav’s Hospital, Trondheim NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 427 Articles NATure GeNeTiCs University Hospital, Trondheim, Norway. 225Department of immunology, Hospital Universitario Doctor Negrín, Las palmas de Gran Canaria, Las palmas, Spain. 226Neurology Department-Hospital Clínic, iDiBApS, Universitat de Barcelona, Barcelona, Spain. 227First Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, Medical School, Athens, Greece. 228LVr-Hospital Essen, Department of psychiatry and psychotherapy, Medical Faculty, University of Duisburg-Essen, Essen, Germany. 229Department of primary Medical Care, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany. 230institute of Medical Biometry, informatics and Epidemiology, University Hospital of Bonn, Bonn, Germany. 231Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway. 232Laboratory for Advanced Hematological Diagnostics, Department of Hematology and Stem Cell Transplant, Vito Fazzi Hospital, Lecce, italy. 233Centro de investigación Biomédica en red de Diabetes y Enfermedades Metabólicas Asociadas, CiBErDEM, Hospital Clínico San Carlos, Madrid, Spain. 234Department of Neurology, University of Bonn, Bonn, Germany. 235Department of Biomedical Sciences, Section of Neuroscience and Clinical pharmacology, University of Cagliari, Cagliari, italy. 236Department of psychiatry, Namsos Hospital, Namsos, Norway. 237Department of internal Medicine and Biostatistics, Erasmus MC, rotterdam, the Netherlands. 238Neurodegenerative Brain Diseases Group, ViB Center for Molecular Neurology, ViB, Antwerp, Belgium. 239Department of Neurology, ErasmusMC, rotterdam, the Netherlands. 240Laboratory for Cognitive Neurology, Department of Neurosciences, University of Leuven, Leuven, Belgium. 241Neurology Department, University Hospitals Leuven, Leuven, Belgium. 242Department of psychiatry and psychotherapy, University Medical Center Goettingen, Goettingen, Germany. 243Department of psychiatry, Harvard Medical School, McLean Hospital, Belmont, MA, USA. 244Department of Neurology and CNr-MAJ, F 76000, Normandy Center for Genomic and personalized Medicine, Normandie University, UNirOUEN, iNSErM U1245, CHU rouen, rouen, France. 245German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany. 246Medical Science Department, iBiMED, Aveiro, portugal. 247Department of Nutrition and Diatetics, Harokopio University, Athens, Greece. 248Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA. 249Neurosciences Area, instituto Biodonostia, San Sebastian, Spain. 250Department of Health Service, University of Washington, Seattle, WA, USA. 251Excellence Cluster on Cellular Stress responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany. 567These authors contributed equally: Céline Bellenguez, Fhari Kuçukali, iris Jansen, Luca Kleineidam, Sonia Moreno-Grau, Najaf Amin, Adam Naj and rafael Campos-Martin. 568These authors jointly supervised this work: Mikko Hiltunen, Kristel Sleegers, Gerard Schellenberg, Cornelia van Duijn, rebecca Sims, Wiesje van der Flier, Agustin ruiz, Alfredo ramirez and Jean-Charles Lambert. ✉e-mail: [email protected]; [email protected] eADB Jan Laczo179,180, Vaclav Matoska252, Maria Serpente124, Francesca Assogna48, Fabrizio Piras48, Federica Piras48, Valentina ciullo48, Jacob Shofany48, carlo Ferrarese38,39, Simona Andreoni38, Gessica Sala38, chiara Paola Zoia38, Maria Del Zompo235, Alberto Benussi66, Patrizia Bastiani253, Mari takalo254, teemu Natunen254, tiina Laatikainen166,178, Jaakko tuomilehto166,178, riitta Antikainen255,256, timo Strandberg255,257, Jaana Lindström178, Markku Peltonen178, richard Abraham258, Ammar Al-chalabi259, Nicholas J. Bass260, carol Brayne261, Kristelle S. Brown262, John collinge187, David craig263, Pangiotis Deloukas264, Nick Fox265, Amy Gerrish265, Michael Gill266, rhian Gwilliam264, Denise Harold267, Paul Hollingworth258, Jarret A. Johnston268, Lesley Jones258, Brian Lawlor266, Gill Livingston260, Simon Lovestone269, Michelle Lupton270,271, Aoibhinn Lynch266, David Mann272, Bernadette McGuinness268, Andrew McQuillin260, Michael c. O’Donovan258, Michael J. Owen258, Peter Passmore268, John F. Powell270,271, Petra Proitsi270,271, Martin rossor265, christopher e. Shaw259, A. David Smith273, Hugh Gurling274, Stephen todd275, catherine Mummery276, Nathalie ryan276, Giordano Lacidogna98, Ad Adarmes-Gómez11,77, Ana Mauleón10, Ana Pancho10, Anna Gailhajenet10, Asunción Lafuente10, D. Macias-García11,77, elvira Martín10, esther Pelejà10, F. carrillo11,77, isabel Sastre Merlín11,134, L. Garrote-espina11,77, Liliana Vargas10, M. carrion-claro11,77, M. Marín96, Ma Labrador11,77, Mar Buendia10, María Dolores Alonso277, Marina Guitart10, Mariona Moreno10, Marta ibarria10, Mt Periñán11,77, Nuria Aguilera10, P. Gómez-Garre11,77, Pilar cañabate10, r. escuela11,77, r. Pineda-Sánchez1,77, r. Vigo-Ortega11,77, S. Jesús11,77, Silvia Preckler10, Silvia rodrigo-Herrero132, Susana Diego10, Alessandro Vacca67, Fausto roveta67, Nicola Salvadori112, elena chipi112, Henning Boecker9,278, christoph Laske279,280, robert Perneczky81,281, costas Anastasiou247, Daniel Janowitz78, rainer Malik78, Anna Anastasiou35, Kayenat Parveen7, carmen Lage282, Sara López-García282, Anna Antonell226, Kalina Yonkova Mihova283, Diyana Belezhanska52, Heike Weber284, Silvia Kochen285, Patricia Solis285, Nancy Medel285, Julieta Lisso285, Zulma Sevillano285, Daniel G. Politis285,286, Valeria cores285,286, carolina cuesta285,286, cecilia Ortiz287, Juan ignacio Bacha287, Mario rios288, Aldo Saenz288, Mariana Sanchez Abalos289, eduardo Kohler290, Dana Lis Palacio291, ignacio etchepareborda291, Matias Kohler291, Gisela Novack292, Federico Ariel Prestia292, Pablo Galeano292, eduardo M. castaño292, Sandra Germani293, NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 428 Articles NATure GeNeTiCs carlos reyes toso293, Matias rojo293, carlos ingino293, carlos Mangone293, David c. rubinsztein294, Stefan teipel295, Nathalie Fievet1, Vincent Deramerourt200, charlotte Forsell143,144, Håkan thonberg143,144, Maria Bjerke89, ellen De roeck89, María teresa Martínez-Larrad296 and Natividad Olivar293 252Department of Clinical Biochemistry, Hematology and immunology, Na Homolce Hospital, prague, Czechia. 253institute of Gerontology and Geriatrics, Department of Medicine, University of perugia, perugia, italy. 254insitute of Biomedicine, University of Eastern Finland, Kuopio, Finland. 255Center for Life Course Health research, University of Oulu, Oulu, Finland. 256Medical research Center Oulu, Oulu University Hospital, Oulu, Finland. 257University of Helsinki and Helsinki University Hospital, Helsinki, Finland. 258Division of psychological Medicine and Clinial Neurosciences, MrC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK. 259institute of psychiatry, psychology and Neuroscience, Kings College London, London, UK. 260Division of psychiatry, University College London, London, UK. 261institute of public Health, University of Cambridge, Cambridge, UK. 262institute of Genetics, Queens Medical Centre, University of Nottingham, Nottingham, UK. 263Ageing Group, Centre for public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast, UK. 264The Wellcome Trust Sanger institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. 265Dementia research Centre, Department of Neurodegenerative Disease, UCL institute of Neurology, London, UK. 266Mercer’s institute for research on Ageing, St James’ Hospital, Dublin, ireland. 267School of Biotechnology, Dublin City University, Dublin, ireland. 268Centre for public Health, School of Medicine, Dentistry and Biomedical Sciences, Queens University, Belfast, UK. 269Department of psychiatry, University of Oxford, Oxford, UK. 270Genetic Epidemiology, QiMr Berghofer Medical research institute, Herston, Queensland, Australia. 271Department of Basic and Clinical Neuroscience, institute of psychiatry, psychology and Neuroscience, Kings College London, London, UK. 272Division of Neuroscience and Experimental psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK. 273Oxford project to investigate Memory and Ageing (OpTiMA), University of Oxford, Level 4, John radcliffe Hospital, Oxford, UK. 274Department of Mental Health Sciences, University College London, London, UK. 275Ageing Group, Centre for public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast, UK. 276Dementia research Centre, UCL, London, UK. 277Servei de Neurologia Hospital Clínic, Universitari de València, Valencia, Spain. 278Department of radiology, University Hospital Bonn, Bonn, Germany. 279German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany. 280Section for Dementia research, Department of psychiatry, Hertie institute for Clinical Brain research, Tübingen, Germany. 281Department of psychiatry and psychotherapy, University Hospital, LMU Munich, Munich, Germany. 282Service of Neurology, University Hospital Marqués de Valdecilla, iDiVAL, University of Cantabria, Santander, Spain. 283Molecular Medicine Center, Department of Medical chemistry and biochemistry, Medical University of Sofia, Sofia, Bulgaria. 284Department of psychiatry, psychosomatics and psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, Germany. 285ENYS (Estudio en Neurociencias y Sistemas Complejos) CONiCET- Hospital El Cruce “Nestor Kirchner”- UNAJ, Buenos Aires, Argentina. 286HiGA Eva perón, Buenes Aires, Argentina. 287Neurología Clinica, Buenes Aires, Argentina. 288Dirección de Atención de Adultos Mayores del Min. Salud Desarrollo Social y Deportes de la pcia. de Mendoza, Mendoza, Argentina. 289Laboratorio de Genética Forense del Ministerio público de la pcia de La pampa, La pampa, Argentina. 290Fundacion Sinapsis, Santa rosa, Argentina. 291Hospital Dr. Lucio Molas, Santa rosa; Fundacion Ayuda Enfermo renal y Alta Complejidad (FErNAC), Santa rosa, Argentina. 292Laboratory of Brain Aging and Neurodegeneration (FiL), Buneos Aires, Argentina. 293Centro de Neuropsiquiatría y Neurología de la Conducta (CENECON), Facultad de Medicina, Universidad de Buenos Aires (UBA), C.A.B.A., Buenos Aires, Argentina. 294Cambridge institute for Medical research and UK Dementia research institute, University of Cambridge, Cambridge, UK. 295German Center for Neurodegenerative Diseases (DZNE), rostock, Germany. 296Centro de investigación Biomédica en red de Diabetes y Enfermedades Metabólicas Asociadas, CiBErDEM, Hospital Clínico San Carlos, Madrid, Spain. Gr@Ace Nuria Aguilera10,11, Mar Buendia10, Amanda cano10, Pilar cañabate10,11, Susana Diego10, Anna Gailhajenet10, Marina Guitart10, Marta ibarria10, Asunción Lafuente10, Juan Macias97, Olalla Maroñas297, elvira Martín10, Mariona Moreno10, raúl Nuñez-Llaves10, clàudia Olivé10, Ana Pancho10, ester Pelejá10, Silvia Preckler10 and Liliana Vargas10 297Grupo de Medicina Xen´omica, Centro Nacional de Genotipado (CEGEN-prB3-iSCiii), Universidad de Santiago de Compostela, Santiago de Compostela, Spain. DeGeScO Astrid D. Adarmes-Gómez11,188, María Dolores Alonso298, Guillermo Amer-Ferrer299, Martirio Antequera37, Juan Andrés Burguera49, Fátima carrillo11,188, Mario carrión-claro11,188, María José casajeros139, Marian Martinez de Pancorbo300, rocío escuela11,188, Lorena Garrote-espina11,188, Pilar Gómez-Garre11,188, Saray Hevilla138, Silvia Jesús11,188, Miguel Angel Labrador espinosa11,188, Agustina Legaz37, Sara López-García11,174, Daniel Macias-García11,188, Salvadora Manzanares299,301, Marta Marín132, Juan Marín-Muñoz37, tamara Marín138, Begoña Martínez37, Victoriana Martínez37, Pablo Martínez-Lage Álvarez302, Maite Mendioroz iriarte303, María teresa Periñán-tocino11,188, rocío Pineda-Sánchez11,188, NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 429 Articles NATure GeNeTiCs Diego real de Asúa304, Silvia rodrigo132, isabel Sastre11,134, Maria Pilar Vicente37, rosario Vigo-Ortega11,188 and Liliana Vivancos37 298Servei de Neurologia, Hospital Clínic Universitari de València, Valencia, Spain. 299Department of Neurology, Hospital Universitario Son Espases, palma, Spain. 300BiOMiCs, país Vasco; Centro de investigación Lascaray, Universidad del país Vasco UpV/EHU, Vitoria-Gasteiz, Spain. 301Fundación para la Formación e investigación Sanitarias de la región de Murcia, palma, Spain. 302Centro de investigación y Terapias Avanzadas, Fundación CiTA-Alzheimer, San Sebastian, Spain. 303Navarrabiomed, pamplona, Spain. 304Hospital Universitario La princesa, Madrid, Spain. eADi Jacques epelbaum305, Didier Hannequin244, Dominique campion92, Vincent Deramecourt200, Nathalie Fievet1, christophe tzourio101, Alexis Brice306 and Bruno Dubois307 305UMr 7179 CNrS/MNHN, Brunoy, France. 306Sorbonne Université, paris Brain institute, ApHp, iNSErM, CNrS, paris, France. 307Department of Neurology, institute of Memory and Alzheimer’s Disease (iM2A), pitié-Salpêtrière Hospital, Ap-Hp, Boulevard de l’Hôpital, paris, France. GerAD Denise Harold267, Paul Hollingworth258, Amy Gerrish265, Amy Williams16, charlene thomas16, chloe Davies16, William Nash16, Kimberley Dowzell16, Atahualpa castillo Morales16,108, Mateus Bernardo-Harrington16,108, James turton308, Jenny Lord308, Kristelle Brown262, emma Vardy309, elizabeth Fisher310, Jason D. Warren310, Martin rossor29, Natalie S. ryan276, rita Guerreiro310, James uphill187, John collinge187, Michelle Lupton270,271, Ammar Al-chalabi259, christopher e. Shaw259, Nick Bass260, richard Abraham258, reinhard Heun311, Heike Kölsch312, Britta Schürmann312, André Lacour9, christine Herold9, Simon Lovestone269, Bernadette McGuinness268, David craig263, Janet A. Johnston268, Michael Gill266, Peter Passmore263, Stephen todd275, John Powell270,271, Petra Proitsi270,271, Yogen Patel313, Angela Hodges311, tim Becker9,314, A. David Smith273, Donald Warden273, Gordon Wilcock273, robert clarke310, Aoibhinn Lynch266, Brian Lawlor266, Andrew McQuillin260, Gill Livingston260, David c. rubinsztein294, carol Brayne261, rhian Gwilliam264, Panagiotis Deloukas264, Yoav Ben-Shlomo315, David Mann272, Nigel M. Hooper272, Stuart Pickering-Brown272, rebecca Sussams316, Nick Warner317, Anthony Bayer318, isabella Heuser319, Dmitriy Drichel320, Norman Klopp321, Manuel Mayhaus322, Matthias riemenschneider322, Sabrina Pinchler322, thomas Feulner322, Wei Gu322, Hendrik van den Bussche229, Michael Hüll323, Lutz Frölich324, H-erich Wichmann321, Karl-Heinz Jöckel325, Michael O’Donovan258, Lesley Jones258 and Michael Owen258 308institute of Genetics, Queen’s Medical Centre, University of Nottingham, Nottingham, UK. 309institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK. 310Department of Neurodegenerative Disease, UCL institute of Neurology, London, UK. 311Department of Old Age psychiatry, institute of psychiatry, psychology and Neuroscience, King’s College London, London, UK. 312Department of psychiatry and psychotherapy, University of Bonn, Bonn, Germany. 313Department of Basic and Clinical Neuroscience, institute of psychiatry, psychology and Neuroscience, King’s College London, London, UK. 314institute for Medical Biometry, informatics and Epidemiology, University of Bonn, Bonn, Germany. 315population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK. 316Division of Clinical Neurosciences, School of Medicine, University of Southampton, Southampton, UK. 317Somerset partnership NHS Trust, Somerset, UK. 318institute of primary Care and public Health, Cardiff University, University Hospital of Wales, Cardiff, UK. 319Department of psychiatry and psychotherapy, Charité University Medicine, Berlin, Germany. 320Cologne Center for Genomics, University of Cologne, Cologne, Germany. 321institute of Epidemiology, Helmholtz Zentrum München, German research Center for Environmental Health, Neuherberg, Munich, Germany. 322Department of psychiatry and psychotherapy, University Hospital, Saarland, Germany. 323Department of psychiatry, University of Freiburg, Freiburg, Germany. 324Central institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany. 325institute for Medical informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany. Demgene Shahram Bahrami46,326, ingunn Bosnes327,328, Per Selnes329 and Sverre Bergh330 NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 430 Articles NATure GeNeTiCs 326Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. 327Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway. 328Department of psychiatry, Hospital Namsos, Nord-Trøndelag Health Trust, Namsos, Norway. 329Department of Neurology, Akershus University Hospital, Lørenskog, Norway. 330Centre for Old Age psychiatry research, innlandet Hospital Trust, Ottestad, Norway. FinnGen Aarno Palotie331, Mark Daly331, Howard Jacob332, Athena Matakidou333, Heiko runz334, Sally John334, robert Plenge335, Mark Mccarthy336, Julie Hunkapiller336, Meg ehm337, Dawn Waterworth337, caroline Fox338, Anders Malarstig339, Kathy Klinger340, Kathy call340, tim Behrens341, Patrick Loerch342, tomi Mäkelä343, Jaakko Kaprio331, Petri Virolainen344, Kari Pulkki344, terhi Kilpi345, Markus Perola345, Jukka Partanen346, Anne Pitkäranta347, riitta Kaarteenaho348, Seppo Vainio348, Miia turpeinen348, raisa Serpi348, tarja Laitinen349, Johanna Mäkelä350, Veli-Matti Kosma351, urho Kujala352, Outi tuovila353, Minna Hendolin353, raimo Pakkanen353, Jeff Waring332, Bridget riley-Gillis332, Jimmy Liu334, Shameek Biswas335, Dorothee Diogo338, catherine Marshall339, Xinli Hu339, Matthias Gossel340, robert Graham341, Beryl cummings342, Samuli ripatti331, Johanna Schleutker344, Mikko Arvas346, Olli carpén347, reetta Hinttala348, Johannes Kettunen348, Arto Mannermaa351, Jari Laukkanen352, Valtteri Julkunen354, Anne remes354, reetta Kälviäinen354, Jukka Peltola355, Pentti tienari356, Juha rinne357, Adam Ziemann332, Jeffrey Waring332, Sahar esmaeeli332, Nizar Smaoui332, Anne Lehtonen332, Susan eaton334, Sanni Lahdenperä334, Janet van Adelsberg335, John Michon336, Geoff Kerchner336, Natalie Bowers336, edmond teng336, John eicher336, Vinay Mehta338, Padhraig Gormley338, Kari Linden339, christopher Whelan339, Fanli Xu337, David Pulford337, Martti Färkkilä356, Sampsa Pikkarainen356, Airi Jussila358, timo Blomster359, Mikko Kiviniemi360, Markku Voutilainen357, Bob Georgantas332, Graham Heap332, Fedik rahimov332, Keith usiskin335, tim Lu6, Danny Oh336, Kirsi Kalpala339, Melissa Miller339, Linda Mccarthy337, Kari eklund356, Antti Palomäki357, Pia isomäki358, Laura Pirilä357, Oili Kaipiainen-Seppänen360, Johanna Huhtakangas359, Apinya Lertratanakul332, Marla Hochfeld335, Nan Bing339, Jorge esparza Gordillo337, Nina Mars331, Margit Pelkonen360, Paula Kauppi356, Hannu Kankaanranta355, terttu Harju359, David close333, Steven Greenberg335, Hubert chen336, Jo Betts337, Soumitra Ghosh337, Veikko Salomaa361, teemu Niiranen361, Markus Juonala357, Kaj Metsärinne357, Mika Kähönen358, Juhani Junttila359, Markku Laakso354, Jussi Pihlajamäki354, Juha Sinisalo356, Marja-riitta taskinen356, tiinamaija tuomi356, Ben challis333, Andrew Peterson336, Audrey chu338, Jaakko Parkkinen339, Anthony Muslin340, Heikki Joensuu356, tuomo Meretoja356, Lauri Aaltonen356, Johanna Mattson356, Annika Auranen355, Peeter Karihtala359, Saila Kauppila359, Päivi Auvinen359, Klaus elenius357, relja Popovic332, Jennifer Schutzman336, Andrey Loboda338, Aparna chhibber338, Heli Lehtonen339, Stefan McDonough339, Marika crohns340, Diptee Kulkarni337, Kai Kaarniranta354, Joni A. turunen356, terhi Ollila356, Sanna Seitsonen356, Hannu uusitalo355, Vesa Aaltonen357, Hannele uusitalo-Järvinen355, Marja Luodonpää359, Nina Hautala359, Stephanie Loomis334, erich Strauss336, Hao chen336, Anna Podgornaia338, Joshua Hoffman337, Kaisa tasanen359, Laura Huilaja359, Katariina Hannula-Jouppi356, teea Salmi358, Sirkku Peltonen356, Leena Koulu356, ilkka Harvima354, Ying Wu9, David choy336, Pirkko Pussinen356, Aino Salminen356, tuula Salo356, David rice356, Pekka Nieminen356, ulla Palotie356, Maria Siponen354, Liisa Suominen354, Päivi Mäntylä354, ulvi Gursoy357, Vuokko Anttonen359, Kirsi Sipilä359, Justin Wade Davis332, Danjuma Quarless332, Slavé Petrovski333, eleonor Wigmore333, chia-Yen chen334, Paola Bronson334, ellen tsai334, Yunfeng Huang334, Joseph Maranville335, elmutaz Shaikho335, elhaj Mohammed335, NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 431 Articles NATure GeNeTiCs Samir Wadhawan362, erika Kvikstad362, Minal caliskan362, Diana chang336, tushar Bhangale336, Sarah Pendergrass336, emily Holzinger338, Xing chen339, Åsa Hedman339, Karen S. King337, clarence Wang340, ethan Xu340, Franck Auge340, clement chatelain340, Deepak rajpal340, Dongyu Liu340, Katherine call340, tai-he Xia340, Matt Brauer341, Mitja Kurki331, Juha Karjalainen331, Aki Havulinna331, Anu Jalanko331, Priit Palta331, Pietro della Briotta Parolo331, Wei Zhou363, Susanna Lemmelä331, Manuel rivas364, Jarmo Harju331, Arto Lehisto331, Andrea Ganna331, Vincent Llorens331, Hannele Laivuori331, Sina rüeger331, Mari e. Niemi331, taru tukiainen331, Mary Pat reeve331, Henrike Heyne331, Nina Mars331, Kimmo Palin365, Javier Garcia-tabuenca366, Harri Siirtola366, tuomo Kiiskinen331, Jiwoo Lee331, Kristin tsuo331, Amanda elliott331, Kati Kristiansson345, Kati Hyvärinen367, Jarmo ritari367, Miika Koskinen347, Katri Pylkäs348, Marita Kalaoja348, Minna Karjalainen348, tuomo Mantere348, eeva Kangasniemi350, Sami Heikkinen351, eija Laakkonen352, csilla Sipeky368, Samuel Heron368, Antti Karlsson344, Dhanaprakash Jambulingam368, Venkat Subramaniam rathinakannan368, risto Kajanne331, Mervi Aavikko331, Manuel González Jiménez331, Pietro della Briotta Parola331, Arto Lehistö331, Masahiro Kanai363, Mari Kaunisto331, elina Kilpeläinen331, timo P. Sipilä331, Georg Brein331, Ghazal Awaisa331, Anastasia Shcherban331, Kati Donner331, Anu Loukola347, Päivi Laiho345, tuuli Sistonen345, essi Kaiharju345, Markku Laukkanen345, elina Järvensivu345, Sini Lähteenmäki345, Lotta Männikkö345, regis Wong345, Hannele Mattsson345, tero Hiekkalinna345, teemu Paajanen345, Kalle Pärn331 and Javier Gracia-tabuenca366 331institute for Molecular Medicine Finland, HiLiFE, University of Helsinki, Helsinki, Finland. 332AbbVie, Chicago, iL, USA. 333Astra Zeneca, Cambridge, UK. 334Biogen, Cambridge, MA, USA. 335Celgene, Summit, NJ, USA. 336Genentech, San Francisco, CA, USA. 337GlaxoSmithKline, Brentford, UK. 338Merck, Kenilworth, NJ, USA. 339pfizer, New York, NY, USA. 340Sanofi, paris, France. 341Maze Therapeutics, San Francisco, CA, USA. 342Janssen Biotech, Beerse, Belgium. 343HiLiFE, University of Helsinki, Helsinki, Finland. 344Auria Biobank, University of Turku, Hospital District of Southwest Finland, Turku, Finland. 345THL Biobank, The National institute of Health and Welfare Helsinki, Helsinki, Finland. 346Finnish red Cross Blood Service, Finnish Hematology registry and Clinical Biobank, Helsinki, Finland. 347Helsinki Biobank, Helsinki University and Hospital District of Helsinki and Uusimaa, Helsinki, Finland. 348Northern Finland Biobank Borealis, University of Oulu, Northern Ostrobothnia Hospital District, Oulu, Finland. 349Oxford Healthy Aging project, Clinical Trial Service Unit, University of Oxford, Oxford, UK. 350Finnish Clinical Biobank Tampere, University of Tampere, pirkanmaa Hospital District, Tampere, Finland. 351Biobank of Eastern Finland, University of Eastern Finland / Northern Savo Hospital District, Kuopio, Finland. 352Central Finland Biobank, University of Jyväskylä, Central Finland Health Care District, Jyväskylä, Finland. 353Business Finland, Helsinki, Finland. 354Northern Savo Hospital District, Kuopio, Finland. 355pirkanmaa Hospital District, Tampere, Finland. 356Hospital District of Helsinki and Uusimaa, Helsinki, Finland. 357Hospital District of Southwest Finland, Turku, Finland. 358pirkanmaa Hospital District, Tampere, Finland. 359Northern Ostrobothnia Hospital District, Oulu, Finland. 360Northern Savo Hospital District, Kuopio, Finland. 361The National institute of Health and Welfare Helsinki, Helsinki, Finland. 362Bristol Myers Squibb, New York, NY, USA. 363Broad institute, Cambridge, MA, USA. 364University of Stanford, Stanford, CA, USA. 365University of Helsinki, Helsinki, Finland. 366University of Tampere, Tampere, Finland. 367Finnish red Cross Blood Service, Helsinki, Finland. 368University of Turku, Turku, Finland. ADGc erin Abner369, Perrie M. Adams370, Alyssa Aguirre371, Marilyn S. Albert372, roger L. Albin373,374,375, Mariet Allen376, Lisa Alvarez377, Liana G. Apostolova378,379, Steven e. Arnold380, Sanjay Asthana381,382,383, craig S. Atwood381,382,383, Gayle Ayres371, clinton t. Baldwin248, robert c. Barber377, Lisa L. Barnes384,385,386, Sandra Barral50,183,186, thomas G. Beach387, James t. Becker388, Gary W. Beecham154, Duane Beekly389, Jennifer e. Below93,390, Penelope Benchek57, Bruno A. Benitez391, David Bennett384,386, John Bertelson392, Flanagan e. Margaret393,394, thomas D. Bird181,395, Deborah Blacker396,397, Bradley F. Boeve398, James D. Bowen399, Adam Boxer400, James Brewer401, James r. Burke402, Jeffrey M. Burns403, Will S. Bush57, Joseph D. 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Kaye461,462, c. Dirk Keene463, Aisha Khaleeq416, ronald Kim446, Janice Knebl431, Neil W. Kowall20,464, Joel H. Kramer465, Pavel P. Kuksa14, Frank M. LaFerla466, James J. Lah467, eric B. Larson468, chien-Yueh Lee14, edward B. Lee14, Alan Lerner57, Yuk Yee Leung14, James B. Leverenz469, Allan i. Levey467, Mingyao Li14, Andrew P. Lieberman470, richard B. Lipton460, Mark Logue248,397,471, constantine G. Lyketsos472, John Malamon14, Douglas Mains431,432, Daniel c. Marson445, Frank Martiniuk473, Deborah c. Mash474, eliezer Masliah401,475, Paul Massman416, Arjun Masurkar428, Wayne c. Mccormick196, Susan M. Mccurry476, Andrew N. McDavid406, Stefan McDonough477, Ann c. McKee20,464, Marsel Mesulam393,394, Jesse Mez20, Bruce L. Miller478, carol A. Miller479, Joshua W. Miller457, thomas J. Montine480, edwin S. Monuki446, John c. Morris404,415,445,481, Amanda J. Myers413, trung Nguyen453, Sid O’Bryant482, John M. Olichney483, Marcia Ory484, raymond Palmer485, Joseph e. Parisi486, Henry L. Paulson373,375, Valory Pavlik416, David Paydarfar371, Victoria Perez420, elaine Peskind487, ronald c. Petersen398, Jennifer e. Phillips-cremins439,488, Aimee Pierce412, Marsha Polk489, Wayne W. Poon421, Huntington Potter490, Liming Qu14, Mary Quiceno491,492, Joseph F. Quinn461,462, Ashok raj405, Murray raskind487, eric M. reiman451,493,494,495, Barry reisberg428,489, Joan S. reisch417, John M. ringman410, erik D. roberson445, Monica rodriguear416, ekaterina rogaeva496, Howard J. rosen400, roger N. rosenberg453, Donald r. royall485, Mark A. Sager382, Mary Sano106, Andrew J. Saykin119,497, Julie A. Schneider384,386,498, Lon S. Schneider410,499, William W. Seeley400, Jin Sha14, Susan H. Slifer154, Scott Small50,186, Amanda G. Smith405, Janet P. Smith417, Yeunjoo e. Song56,57, Joshua A. Sonnen463, Salvatore Spina435, Peter St George-Hyslop500,501, robert A. Stern20, Alan B. Stevens484,502,503, Stephen M. Strittmatter504, David Sultzer505, russell H. Swerdlow403, rudolph e. tanzi441, Jeffrey L. tilson506, John Q. trojanowski14, Juan c. troncoso507, Debby W. tsuang395,487, Otto Valladares14, Vivianna M. Van Deerlin14, Linda J. van eldik122, robert Vassar393,394, Harry V. Vinters410,508, Jean-Paul Vonsattel50, Sandra Weintraub509, Kathleen A. Welsh-Bohmer402,510, Patrice L. Whitehead154, ellen M. Wijsman196,456,511, Kirk c. Wilhelmsen408, Benjamin Williams411, Jennifer Williamson50, Henrik Wilms420, thomas S. Wingo467, thomas Wisniewski512,513, randall L. Woltjer514, NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 433 Articles NATure GeNeTiCs Martin Woon392, clinton B. Wright515, chuang-Kuo Wu420, Steven G. Younkin376,423, chang-en Yu196, Lei Yu384,386, Yuanchao Zhang442, Yi Zhao48 and Xiongwei Zhu516 369Sanders-Brown Center on Aging, Department of Epidemiology, College of public Health, University of Kentucky, Lexington, KY, USA. 370Department of psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA. 371Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, USA. 372Department of Neurology, Johns Hopkins University, Baltimore, MD, USA. 373Department of Neurology, University of Michigan, Ann Arbor, Mi, USA. 374Geriatric research, Education and Clinical Center (GrECC), VA Ann Arbor Healthcare System (VAAAHS), Ann Arbor, Mi, USA. 375Michigan Alzheimer’s Disease Center, University of Michigan, Ann Arbor, Mi, USA. 376Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA. 377Department of pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, USA. 378Departments of Neurology, radiology, and Medical and Molecular Genetics, indiana University School of Medicine, indianapolis, iN, USA. 379indiana Alzheimer’s Disease research Center, indiana University School of Medicine, indianapolis, iN, USA. 380Department of psychiatry, perelman School of Medicine, University of pennsylvania, philadelphia, pA, USA. 381Geriatric research, Education and Clinical Center (GrECC), University of Wisconsin, Madison, Wi, USA. 382Department of Medicine, University of Wisconsin, Madison, Wi, USA. 383Wisconsin Alzheimer’s Disease research Center, Madison, Wi, USA. 384Department of Neurological Sciences, rush University Medical Center, Chicago, iL, USA. 385Department of Behavioral Sciences, rush University Medical Center, Chicago, iL, USA. 386rush Alzheimer’s Disease Center, rush University Medical Center, Chicago, iL, USA. 387Civin Laboratory for Neuropathology, Banner Sun Health research institute, phoenix, AZ, USA. 388Departments of psychiatry, Neurology, and psychology, University of pittsburgh School of Medicine, pittsburgh, pA, USA. 389National Alzheimer’s Coordinating Center, University of Washington, Seattle, WA, USA. 390Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA. 391Department of psychiatry and Hope Center program on protein Aggregation and Neurodegeneration, Washington University School of Medicine, St. Louis, MO, USA. 392Department of psychiatry, University of Texas at Austin/Dell Medical School, Austin, TX, USA. 393Department of pathology, Northwestern University Feinberg School of Medicine, Chicago, iL, USA. 394Cognitive Neurology and Alzheimer’s Disease Center, Northwestern University Feinberg School of Medicine, Chicago, iL, USA. 395VA puget Sound Health Care System/GrECC, Seattle, WA, USA. 396Department of Epidemiology, Harvard School of public Health, Boston, MA, USA. 397Department of psychiatry, Massachusetts General Hospital/ Harvard Medical School, Boston, MA, USA. 398Department of Neurology, Mayo Clinic, rochester, MN, USA. 399Swedish Medical Center, Seattle, WA, USA. 400Department of Neurology, University of California San Francisco, San Francisco, CA, USA. 401Department of Neurosciences, University of California San Diego, La Jolla, CA, USA. 402Department of Medicine, Duke University, Durham, NC, USA. 403University of Kansas Alzheimer’s Disease Center, University of Kansas Medical Center, Kansas City, KS, USA. 404Department of pathology and immunology, Washington University, St. Louis, MO, USA. 405USF Health Byrd Alzheimer’s institute, University of South Florida, Tampa, FL, USA. 406Fred Hutchinson Cancer research Center, Seattle, WA, USA. 407Mental Health and Behavioral Science Service, Bruce W. Carter VA Medical Center, Miami, FL, USA. 408Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 409Neurogenetics program, University of California, Los Angeles, Los Angeles, CA, USA. 410Department of Neurology, University of Southern California, Los Angeles, CA, USA. 411Section of Gerontology and Geriatric Medicine research, Wake Forest School of Medicine, Winston-Salem, NC, USA. 412Department of Neurology, University of California, irvine, irvine, CA, USA. 413Department of psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, FL, USA. 414NeuroGenomics and informatics, Washington University in St. Louis, St. Louis, MO, USA. 415Department of psychiatry, Washington University in St. Louis, St Louis, MO, USA. 416Alzheimer’s Disease and Memory Disorders Center, Baylor College of Medicine, Houston, TX, USA. 417Department of population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, Texas, USA. 418Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, USA. 419Department of Neurology, University of California, Davis, Sacramento, CA, USA. 420Departments of Neurology, pharmacology and Neuroscience, Texas Tech University Health Science Center, Lubbock, TX, USA. 421institute for Memory impairments and Neurological Disorders, University of California, irvine, irvine, CA, USA. 422Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA. 423Department of Neurology, Mayo Clinic, Jacksonville, FL, USA. 424rush institute for Healthy Aging, Department of internal Medicine, rush University Medical Center, Chicago, iL, USA. 425Office of Strategy and Measurement, University of North Texas Health Science Center, Fort Worth, TX, USA. 426Department of pathology, University of Alabama at Birmingham, Birmingham, AL, USA. 427Department of Neurology, indiana University, indianapolis, iN, USA. 428Department of psychiatry, New York University, New York, NY, USA. 429C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Charlestown, MA, USA. 430Department of Neuroscience, ronald M. Loeb Center for Alzheimer’s Disease, icahn School of Medicine at Mount Sinai, New York, NY, USA. 431Department of Health Behavior and Health Systems, University of North Texas Health Science Center, Fort Worth, TX, USA. 432Department of Health Management and policy, School of public Health, University of North Texas Health Science Center, Fort Worth, TX, USA. 433Department of pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA. 434Emory Alzheimer’s Disease Center, Emory University, Atlanta, GA, USA. 435Department of pathology and Laboratory Medicine, indiana University, indianapolis, iN, USA. 436Department of radiology, University of Washington, Seattle, WA, USA. 437Center for Spatial and Functional Genomics, Division of Human Genetics, Children’s Hospital of philadelphia, philadelphia, pA, USA. 438Department of pediatrics, perelman School of Medicine, University of pennsylvania, philadelphia, pA, USA. 439Department of Genetics, perelman School of Medicine, University of pennsylvania, philadelphia, pA, USA. 440Division of Genetics, Department of Medicine and partners Center for personalized Genetic Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA. 441Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA. 442Center for Applied Genomics, Children’s Hospital of philadelphia, philadelphia, pA, USA. 443Division of Human Genetics, Department of pediatrics, perelman School of Medicine, University of pennsylvania, philadelphia, pA, USA. 444Department of pathology (Neuropathology), University of pittsburgh, pittsburgh, pA, USA. 445Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA. 446Department of pathology and Laboratory Medicine, University of California irvine, irvine, CA, USA. 447Department of Epidemiology and population Health, Stanford University, Stanford, CA, USA. 448Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA. 449Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA. 450Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA. 451Neurogenomics Division, Translational Genomics research institute, phoenix, AZ, USA. 452Department of pathology, Duke University, Durham, NC, USA. 453Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA. 454Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA. 455Hope Center program on protein Aggregation and Neurodegeneration, Washington University School of Medicine, St. Louis, MO, USA. 456Department of Genome Sciences, University of Washington, Seattle, WA, USA. 457Department of pathology and Laboratory Medicine, University of California, Davis, Sacramento, CA, USA. 458Department of Human Genetics, University of pittsburgh, pittsburgh, pA, USA. 459Alzheimer’s Disease research Center, University of pittsburgh, pittsburgh, pA, USA. 460Department of Neurology, Albert Einstein College of Medicine, New York, NY, USA. 461Department of Neurology, Oregon Health and Science University, portland, Or, USA. 462Department of Neurology, portland Veterans Affairs Medical Center, portland, Or, USA. 463Department of Laboratory Medicine and pathology, University of Washington, Seattle, WA, USA. 464Department of pathology, Boston NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 434 Articles NATure GeNeTiCs University, Boston, MA, USA. 465Department of Neuropsychology, University of California San Francisco, San Francisco, CA, USA. 466Department of Neurobiology and Behavior, University of California irvine, irvine, CA, USA. 467Department of Neurology, Emory University, Atlanta, GA, USA. 468Kaiser permanente Washington Health research institute, Seattle, WA, USA. 469Cleveland Clinic Lou ruvo Center for Brain Health, Cleveland Clinic, Cleveland, OH, USA. 470Department of pathology, University of Michigan, Ann Arbor, Mi, USA. 471National Center for pTSD at Boston VA Healthcare System, Boston, MA, USA. 472Department of psychiatry, Johns Hopkins University, Baltimore, MD, USA. 473Department of Medicine (pulmonary), New York University, New York, NY, USA. 474Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, USA. 475Department of pathology, University of California San Diego, La Jolla, CA, USA. 476School of Nursing Northwest research Group on Aging, University of Washington, Seattle, WA, USA. 477pfizer Worldwide research and Development, New York, NY, USA. 478Weill institute for Neurosciences, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA. 479Department of pathology, University of Southern California, Los Angeles, CA, USA. 480Department of pathology, Stanford University School of Medicine, Stanford, CA, USA. 481Department of Neurology, Washington University at St. Louis, St. Louis, MO, USA. 482institute for Translational research, University of North Texas Health Science Center, Fort Worth, TX, USA. 483Center for Mind and Brain and Department of Neurology, University of California, Davis, Sacramento, CA, USA. 484Center for population Health and Aging, Texas A&M University Health Science Center, Lubbock, TX, USA. 485Department of Family and Community Medicine, University of Texas Health Science Center San Antonio, San Antonio, TX, USA. 486Department of Laboratory Medicine and pathology, Mayo Clinic, rochester, MN, USA. 487Department of psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, USA. 488Department of Bioengineering, University of pennsylvania, philadelphia, pA, USA. 489Alzheimer’s Disease Center, New York University, New York, NY, USA. 490Department of Neurology, University of Colorado School of Medicine, Aurora, CO, USA. 491Department of internal Medicine and Geriatrics, University of North Texas Health Science Center, Fort Worth, TX, USA. 492Department of Medical Education, TCU/UNTHSC School of Medicine, Fort Worth, TX, USA. 493Arizona Alzheimer’s Consortium, phoenix, AZ, USA. 494Banner Alzheimer’s institute, phoenix, AZ, USA. 495Department of psychiatry, University of Arizona, phoenix, AZ, USA. 496Tanz Centre for research in Neurodegenerative Disease, University of Toronto, Toronto, Ontario, Canada. 497Department of radiology and imaging Sciences, indiana University, indianapolis, iN, USA. 498Department of pathology (Neuropathology), rush University Medical Center, Chicago, iL, USA. 499Department of psychiatry, University of Southern California, Los Angeles, CA, USA. 500Cambridge institute for Medical research, University of Cambridge, Cambridge, UK. 501Faculty of Medicine, Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada. 502Center for Applied Health research, Baylor Scott & White Health, Temple, TX, USA. 503College of Medicine, Texas A&M University Health Science Center, College Station, TX, USA. 504program in Cellular Neuroscience, Neurodegeneration and repair, Yale University School of Medicine, New Haven, CT, USA. 505Department of psychiatry and Human Behavior, University of California, irvine, irvine, CA, USA. 506renaissance Computing institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 507Department of pathology, Johns Hopkins University, Baltimore, MD, USA. 508Department of pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA. 509Department of psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, iL, USA. 510Department of psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA. 511Department of Biostatistics, University of Washington, Seattle, WA, USA. 512Department of psychiatry, New York University Grossman School of Medicine, New York, NY, USA. 513Center for Cognitive Neurology and Departments of Neurology and pathology, New York University Grossman School of Medicine, New York, NY, USA. 514Department of pathology, Oregon Health and Science University, portland, Or, USA. 515Evelyn F. McKnight Brain institute, Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, USA. 516Department of pathology, Case Western reserve University, Cleveland, OH, USA. cHArGe Hieab Adams1, rufus O. Akinyemi517, Muhammad Ali518, Nicola Armstrong519, Hugo J. Aparicio109, Maryam Bahadori130, James t. Becker520, Monique Breteler521, Daniel chasman522, Ganesh chauhan523, Hata comic12, Simon cox524, Adrienne L. cupples21, Gail Davies525, charles S. Decarli526, Marie-Gabrielle Duperron527, Josée Dupuis21, tavia evans12, Frank Fan528, Annette Fitzpatrick529, Alison e. Fohner23, Mary Ganguli528, Mirjam Geerlings530, Stephen J. Glatt531, Hector M. Gonzalez532, Monica Goss130, Hans Grabe533, Mohamad Habes534, Susan r. Heckbert535, edith Hofer536, elliot Hong537, timothy Hughes130, Xueqiu Jian130, tiffany F. Kautz538, Maria Knol12, William Kremen12, Paul Lacaze539, Jari Lahti540, Quentin Le Grand527, elizabeth Litkowski541, Shuo Li21, Dan Liu521, Xuan Liu21, Marisa Loitfelder542, Alisa Manning543, Pauline Maillard544, riccardo Marioni545, Bernard Mazoyer546, Debora Melo van Lent130, Hao Mei547, Aniket Mishra527, Paul Nyquist548, Jeffrey O’connell537, Yash Patel549, tomas Paus550, Zdenka Pausova551, Katri raikkonen-talvitie540, Moeen riaz539, Stephen rich539, Jerome rotter552, Jose romero553, Gena roshchupkin12, Yasaman Saba554, Murali Sargurupremraj554, Helena Schmidt554, reinhold Schmidt555, Joshua M. Shulman556, Jennifer Smith557, Hema Sekhar527, reddy rajula527, Jean Shin558, Jeannette Simino559, eeva Sliz559, Alexander teumer560, Alvin thomas561, Adrienne tin559, elliot tucker-Drob562, Dina Vojinovic12, Yanbing Wang9, Galit Weinstein563, Dylan Williams564, Katharina Wittfeld565, Lisa Yanek548 and Yunju Yang566 517Centre for Genomic and precision Medicine, College of Medicine, Ui, ibadan, Nigeria. 518Washington University at St. Louis, St. Louis, MO, USA. 519Mathematics and Statistics, Curtin University, perth, Western Australia, Australia. 520Departments of psychiatry, Neurology, and psychology, University of pittsburgh, pittsburgh, pA, USA. 521population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. 522Brigham and Women’s Hospital, Harvard University, Boston, MA, USA. 523iNSErM U1219, University of Bordeaux, Bordeaux, France. 524University of Edinburgh, NAture GeNeticS | VOL 54 | ApriL 2022 | 412–436 | www.nature.com/naturegenetics 435 Articles NATure GeNeTiCs Edinburgh, UK. 525Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK. 526Department of Neurology and Center for Neuroscience, University of California, Davis, Davis, CA, USA. 527Bordeaux population Health research Center, Team ViN-TAGE, UMr 1219, University of Bordeaux, iNSErM, Bordeaux, France. 528University of pittsburgh, pittsburgh, pA, USA. 529Department of Family Medicine, University of Washington, Seattle, WA, USA. 530University Medical Center Utrecht, Utrecht, the Netherlands. 531psychiatric Genetic Epidemiology & Neurobiology Laboratory (psychGENe Lab), Department of psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA. 532University of California, San Diego, San Diego, CA, USA. 533Department of psychiatry and psychotherapy, University Medicine Greifswald, Greifswald, Germany. 534Department of radiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA. 535School of public Health, University of Texas Health Science Center at Houston, Houston, TX, USA. 536Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria. 537University of Maryland, College park, MD, USA. 538Department of General Medicine, University of Texas Health Science Center, San Antonio, TX, USA. 539Monash University Clayton Campus, Mebourne, Victoria, Australia. 540University of Helsinki, Helsinki, Finland. 541University of Colorado Anschutz Medical Center, Aurora, CO, USA. 542Medical University of Graz, Graz, Austria. 543Massachusetts General Hospital, Harvard University, Cambridge, MA, USA. 544imaging of Dementia and Aging (iDeA) Laboratory, Department of Neurology, University of California, Davis, Davis, CA, USA. 545University of Staffmail, Edinburgh, UK. 546University of Bordeaux, iMN, Bordeaux, France. 547University of Mississippi Medical Center, Jackson, MS, USA. 548GeneSTAr research program, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 549University of Toronto, Toronto, Ontario, Canada. 550Departments of psychiatry & Neuroscience, Centre Hospitalier Universitaire Saint-Justine, University of Montreal, Montreal, Quebec, Canada. 551Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. 552institute for Translational Genomics and population Sciences, Los Angeles Biomedical research institute and pediatrics at Harbor-UCLA Medical Center, Torrance, CA, USA. 553Boston Medical Center, Boston, MA, USA. 554Gottfried Schatz research Center, Department of Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria. 555Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria. 556Departments of Neurology, Molecular & Human Genetics, and Neuroscience and program in Developmental Biology, Baylor College of Medicine, Houston, TX, USA. 557Department of Epidemiology, School of public Health, University of Michigan, Ann Arbor, Mi, USA. 558Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. 559University of Mississippi Medical Center, Jackson, MS, USA. 560institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. 561University of North Carolina, Chapel Hill, NC, USA. 562University of Texas, Austin, TX, USA. 563Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria. 564Karolinska institute, Stockholm, Sweden. 565German Center for Neurodegenerative Diseases (DZNE), Site rostock/ Greifswald, Greifswald, Germany. 566institute of Molecular Medicine, University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX, U SA . 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