Gene-Based Analysis in HRC Imputed Genome Wide

bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Gene-Based Analysis in HRC Imputed Genome Wide Association Data Identifies Three Novel Genes For Alzheimer’s Disease Emily Baker1, Rebecca Sims1, Ganna Leonenko1, Aura Frizzati1, Janet Harwood1, Detelina Grozeva1, GERAD/PERADES+, IGAP consortia+, Kevin Morgan2, Peter Passmore3, Clive Holmes4, John Powell5, Carol Brayne6, Michael Gill7, Simon Mead8, Reiner Heun9, Paola Bossù10, Gianfranco Spalletta11, Alison Goate12, Carlos Cruchaga13, Cornelia van Duijn14, Wolfgang Maier9,15, Alfredo Ramirez9,16, Lesley Jones1, John Hardy17, Dobril Ivanov18, Matthew Hill18, Peter Holmans1, Nicholas Allen18, Paul Morgan18, Julie Williams1,18*, Valentina Escott-Price1,18*

1Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK, 2Institute of Genetics, Queens Medical Centre, University of Nottingham, UK, 3Ageing Group, Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queens University Belfast, UK, 4Division of Clinical Neurosciences, School of Medicine, University of Southampton, Southampton, UK, 5Kings College London, Institute of Psychiatry, Department of Neuroscience, De Crespigny Park, Denmark Hill, London, 6Institute of Public Health, University of Cambridge, Cambridge, UK, 7Mercers Institute for Research on Aging, St. James Hospital and Trinity College, Dublin, Ireland, 8MRC Prion Unit, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK, 9Department of Psychiatry and Psychotherapy, University of Bonn, 53127 Bonn, Germany, 10Experimental Neuropsychobiology Laboratory, IRCCS Santa Lucia Foundation, Department of Clinical and Behavioral Neurology, Rome, Italy, 11Functional Genomics Center Zurich, ETH/University of Zurich, 12Neuroscience Department, Icahn School of Medicine at Mount Sinai, New York, USA, 13Departments of Psychiatry, Neurology and Genetics, Washington University School of Medicine, St Louis, MO 63110, USA, 14Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands, 15German Centre for Neurodegenerative Diseases (DZNE), Bonn, 53175, Germany, 16Institute of Human Genetics, University of Bonn, 53127, Bonn, Germany, 17Department of Molecular Neuroscience and Reta Lilla Weston Laboratories, Institute of Neurology, London, UK, 18Dementia Research Institute, Cardiff University, UK

∗ Correspondence to: Valentina Escott-Price and Julie Williams, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK; E-mail: [email protected]; Telephone: +44 (0)29 2068 8429

+ Data used in the preparation of this article were obtained from the Genetic and Environmental Risk for Alzheimer’s disease (GERAD) (which now incorporates the Defining Genetic, Polygenic and Environmental Risk for Alzheimer’s Disease using multiple powerful cohorts, focused Epigenetics and Stem cell metabolomics, PERADES consortium) and the International Genomics of Alzheimer’s Disease (IGAP) Consortia. For details of these consortia, see Appendix I and the Supplementary material. bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Abstract A novel POLARIS gene-based analysis approach was employed to compute gene-based polygenic risk score (PRS) for all individuals in the latest HRC imputed GERAD (N cases=3,332 and N controls=9,832) data using the International Genomics of Alzheimer’s Project summary statistics (N cases=13,676 and N controls=27,322, excluding GERAD subjects) to identify the SNPs and weight their risk alleles for the PRS score. SNPs were assigned to known, protein coding genes using GENCODE (v19). SNPs are assigned using both 1) no window around the gene and 2) a window of 35kb upstream and 10kb downstream to include transcriptional regulatory elements. The overall association of a gene is determined using a logistic regression model, adjusting for population covariates.

Three novel gene-wide significant genes were determined from the POLARIS gene-based analysis using a gene window; PPARGC1A, RORA and ZNF423. The ZNF423 gene resides in an Alzheimer’s disease (AD)- specific protein network which also includes other AD-related genes. The PPARGC1A gene has been linked to energy metabolism and the generation of amyloid beta plaques and the RORA has strong links with genes which are differentially expressed in the hippocampus. We also demonstrate no enrichment for genes in either loss of function intolerant or conserved noncoding sequence regions.

Keywords: Gene, POLARIS, Alzheimer’s disease, PPARGC1A, RORA, ZNF423

Introduction Late Onset Alzheimer’s disease (LOAD) is a devastating neurodegenerative condition with a significant genetic heritability (Gatz et al. [2006]). The apolipoprotein E (APOE) gene is the strongest genetic risk factor for LOAD (Strittmatter et al. [1993]). Subsequently, more genes were found to be associated with AD development. The Genetic and Environmental Risk in Alzheimer’s Disease Consortium (GERAD) published a Genome-Wide Association Study (GWAS) that identified novel variants in CLU and PICALM which were associated with AD (Harold et al. [2009]). Concurrently, the European Alzheimer’s Disease Initiative (EADI) identified the CR1 and CLU loci to associate with AD (Lambert et al. [2013]). Subsequent publications by GERAD, the Alzheimer’s Disease Genetic Consortium (ADGC) and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium identified a further 5 novel loci (Hollingworth et al. [2011], Naj et al. [2011], Seshadri et al. [2010]). The International Genomics of Alzheimer’s Project (IGAP) (Lambert et al. [2013]) consortium is an amalgamation of these four different genetic groups (GERAD, EADI, ADGC and CHARGE). Meta-analysis of the 4 GWAS datasets determined 11 novel variants associated with AD were determined. A gene-based analysis has been undertaken in the IGAP AD data using Brown’s method (Brown [1975]). This approach determined two additional novel genes; TP53INP1 and IGHV1-67 (Escott-Price et al. [2014]). Additionally, low frequency risk variants have been identified through next generation sequencing (TREM2) (Guerreiro et al. [2013]) and an whole- exome association study (PLCG2, TREM2 and ABI3 (Sims et al. [2017])).

Set-based analysis is an alternative to Genome-Wide Association Study (GWAS) analyses, which considers the association of an individual Single Nucleotide Polymorphism (SNP) with disease. Set-based analyses provide more power due to the aggregate effect of multiple SNPs being larger than that of individual SNPs. For example, determining the association of genes rather than SNPs, is beneficial since genes are more robust across different populations (Li et al. [2011]). Set-based analyses are being widely used in the field and as expected, are able to identify novel genes or pathways associated with disease. Pathways clustering in eight areas of biology have been found to be associated with AD using the ALIGATOR (Holmans et al. [2009]) algorithm (Jones et al. [2010]) (Jones et al. [2015]). Additionally, 134 gene-sets have been identified as being associated with Schizophrenia (SZ) that are related to nervous system function and development, where gene-sets are defined from single gene functional studies (Pocklington et al. [2015]). Other gene and gene-set analyses were considered in a SZ study investigating exomic variation which determined an enrichment in genes whose messenger ribonucleic acid (mRNA) binds to fragile X mental retardation protein (FMRP) and Loss of Function (LoF) intolerant genes (Leonenko et al. [2017]).

The aim of the current study is to identify novel genes associated with AD using the largest up-to-date reference SNP panel, the most accurate imputation software and the latest published gene-based analysis approach. In this study, we used the GERAD data (Harold et al. [2009]) which have recently been imputed using the latest Haplotype Reference Consortium data (HRC). Polygenic Linkage disequilibrium- bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Adjusted Risk Score (POLARIS) (Baker et al. [2018]) is a powerful gene-based method which produces a risk score per person per gene, adjusts for Linkage Disequilibrium (LD) between SNPs and informs the analysis with summary statistics from an external data set. POLARIS, unlike standard Polygenic Risk Score (PRS) does not require data to be pruned for LD prior to analysis, so is able to incorporate information from a larger number of SNPs. We employed the POLARIS approach (Baker et al. [2018]) and using the individual genotypes in the GERAD imputed data, produced the risk score for each individual for every gene considered. The IGAP (Lambert et al. [2013]) SNP summary statistic data, where the individuals from GERAD study were excluded, were used to generate the gene-based PRS. Furthermore, previous studies (e.g. Pardinas et al. [2018]) have suggested that genes associated with SZ are evolutionary constrained, likely due to functional importance during the neurodevelopmental stages. Since AD is a post-reproductive disorder, we hypothesised and tested whether genes associated with AD reside in conserved noncoding sequences or whether there is an enrichment of genes which are LoF intolerant. Methods The Haplotype Reference Consortium (HRC), version r1.1 2016, was used to impute GERAD genotype data on the Michigan Imputation Server (Das et al. [2016]), which to date, allows most accurate imputation of genetic variants. Imputed genotype probabilities (also known as dosages) were converted to the most probable genotype with a probability threshold of 0.9 or greater. SNPs were removed if: their imputation INFO-score<0.4, minor allele frequency (MAF)<0.01, missingness of genotypes≥0.05 or HWE<10-6. A total of 6,119,694 variants were retained. To correct for population structure and genotyping differences, all analyses were adjusted for gender and the top 15 principal components.

POLARIS was applied to this GERAD (3,332 cases, 9,832 controls) imputed data, using the IGAP (Lambert et al. [2013]) data (17,008 cases, 37,154 controls) excluding GERAD subjects (IGAPnoGERAD) as an external dataset to improve power. There were 3,169,839 SNPs in common between imputed GERAD and IGAP summary statistics data. The GERAD imputed data contain individual genotypes for every SNP, enabling the production of a risk score per person, and the IGAPnoGERAD data contains effect sizes for every SNP, which are used to weight the risk score. A gene-based risk score was produced for every individual in the GERAD data.

POLARIS adjusts for LD between SNPs and therefore, the SNPs were not pruned for LD and the entire data were used in this analysis. POLARIS adjusts for LD by using spectral decomposition of the correlation matrix between SNPs. Such a matrix was derived for each gene using the individual genotypes from the GERAD imputed data. To ensure that SNP alleles were coded in the same direction across both independent datasets; IGAPnoGERAD and imputed GERAD if alleles in IGAPnoGERAD were coded in the opposite direction to those in GERAD, the summary effect size for the SNP was inverted. SNPs with alleles AT, TA, CG or GC were excluded. bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

MAGMA (de Leeuw et al. [2015]) software offers an alternative approach to gene-based analyses. It can either be applied to summary statistics, or to the individual genotypes. We run both options of MAGMA software in our GERAD HRC imputed data. These analyses however cannot use additional (IGAPnoGERAD) information, but include all SNPs (N=6,119,694), as merging with the IGAPnoGERAD summary statistic data is not required.

SNPs were assigned to genes using GENCODE (v19) gene models (Harrow et al. [2012]). Only genes with known gene status and those marked as protein coding were used. Two different gene windows were considered, the first used no window around the gene, only SNPs within the start and end position of the gene were included, and the second considered SNPs which were within 35kb upstream and 10kb downstream of the gene. These windows were used since it is likely to contain transcriptional regulatory elements (Network and Consortium Pathway Analysis Subgroup of Psychiatric Genomics [2015]). SNPs which belong to multiple genes were assigned to all those genes. In the HRC imputed GERAD data, 1,122,570 SNPs were assigned to 17,072 distinct genes when no gene window was used and 2,296,690 SNPs were assigned to 18,087 genes when the gene window was used.

A POLARIS score was produced for each of these genes, and the overall association of the gene with AD is determined using a logistic regression model, adjusting for population covariates.

It was then assessed whether genes determined from the gene-based analysis were enriched in conserved regions; both for genes which are evolutionary constrained LoF intolerant and those which reside in conserved noncoding sequences. Genes which are evolutionary constrained were determined using the Exome Aggregation Consortium (ExAC) which contains high quality exome sequence data for 60,706 subjects (Lek et al. [2016]). This database contains a list of genes, so the number of genes from our analysis which reside in this list were determined. The conserved noncoding regions were defined from Babarinde et al. [2016], this data contains genomic locations for the conserved noncoding regions. Genes from our gene-based analysis which overlap these regions were determined. These regions are less likely to harbour variants of a strong effect or are less prone to variation (Babarinde et al. [2016]). The number of genes from the gene-based analysis with a p-value below either a nominal (0.05) or gene-wide threshold (2.5 × 10-6) and were in conserved regions were determined. The 2x2 contingency tables (not presented) have columns containing the number of genes with p-values above and below the p-value threshold and the rows show the number of genes in/out of conserved regions. The strength of association between genes residing in conserved regions and gene p-value was assessed using a chi- squared test (or Fisher’s exact, when the cell counts in the 2x2 table were small). Since the same SNPs may be assigned to multiple genes, it is not possible to assume independence between genes. Therefore, prior to the analysis, genes within 250kb of one another were removed, retaining the most significantly associated gene. However, including all genes regardless of LD (not presented) does not change the result. bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Results For the imputed GERAD data, the SNPs are assigned to 17,072 genes. Of these genes, six reach gene- wide significance when no gene window is used. These genes are CLU, BCL3, PVRL2, TOMM40, APOE and CLPTM1 (see details in Table I); these have all been previously identified as being associated with AD (Harold et al. [2009], Lambert et al. [2013]). The majority of these associations are influenced by APOE since these genes are close in location to APOE. These results are shown on the Manhattan plot in Figure 1, the gene-wide significant genes are shown in green, and those with a suggestive p-value (2.5 × 10-6 < p < 0.00001) are shown in blue; these are DAB1, ZNF35 and RORA.

Table I: Gene-Wide Significant Genes from POLARIS Gene-based Analysis in AD Imputed Data

POLARIS

Chr Gene No. of SNPs Beta SE P-value

8 CLU 25 0.521 0.1048 6.8x10-7

19 BCL3 5 0.927 0.1499 6.1x10-10

19 PVRL2 95 0.637 0.0532 5.7x10-33

19 TOMM40 20 0.454 0.0351 2.9x10-38

19 APOE 1 2.247 0.2679 4.9x10-17

19 CLPTM1 93 0.461 0.0965 1.8x10-6

Figure 1: Manhattan Plot for the POLARIS Gene-Based Analysis in Imputed GERAD data

10 ↑ APOE

CLU 6 ZNF35 RORA ) DAB1

(

- 4

0 1 2 3 4 5 6 7 8 9 11 13 15 18 21

Chromosome

MAGMA can be applied to both individual genotype data (termed MAGMA-PCA) or to summary statistic data (termed MAGMA-SUMMARY). The gene-wide significant genes from the imputed GERAD data using MAGMA-PCA are in Table II. This method finds three genes below the gene-wide threshold, all of which are in the APOE region; BCL3, PVRL2 and TOMM40 (Harold et al. [2009], Lambert et al. [2013]).

Table II: Gene-Wide Significant Genes from MAGMA-PCA Gene-based Analysis in GERAD Imputed Data

Chr Gene No. of SNPs MAGMA-PCA P-value

19 BCL3 5 2.7x10-8

19 PVRL2 92 4.9x10-35

19 TOMM40 20 1.6x10-48

Table III shows the gene-wide significant results for the gene-based analysis in the imputed GERAD using MAGMA-SUMMARY. This method uses the summary statistics of the imputed GERAD data rather than the individual genotypes. This analysis determines four gene-wide significant genes, all of which have bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

been previously identified or are part of the APOE region (Harold et al. [2009], Lambert et al. [2013]).

Chr Gene No. of SNPs MAGMA-SUMM P-value

8 CLU 25 1.5x10-6

19 BCL3 5 9.5x10-7

19 PVRL2 95 1.6x10-13

19 TOMM40 20 4.0x10-26

Table III: Gene-Wide Significant Genes from MAGMA-SUMM Gene-based Analysis in GERAD Imputed Data

This analysis was repeated using a window around the gene of 35kb upstream and 10kb downstream since transcriptional regulatory elements are likely to be contained within this window (Network and Consortium Pathway Analysis Subgroup of Psychiatric Genomics [2015]). The gene-based results for the 18,087 genes are plotted on a Manhattan plot in Figure 2. The 12 gene-wide significant genes from this analysis are shown in Table IV. Again, a large number of genes reside on chromosome 19 and these are likely influenced by the large effect of APOE. Three novel genes have been identified from this analysis: PPARGC1A, RORA and ZNF423. The PPARGC1A gene has been linked to energy metabolism and the generation of amyloid beta plaques (Katsouri et al. [2016]) and has potential relevance to the human aging process. The RORA gene has strong links with genes which are differentially expressed in the hippocampus (Acquaah-Mensah et al. [2015]). The ZNF423 gene resides in an AD-specific protein network which also includes other AD-related genes such as APOE, CLU, ABCA7, TREM2 etc. (Hu et al. [2017]). In addition, the SCARA3 gene overlaps CLU which has previously been identified as being associated with AD (Harold et al. [2009], Lambert et al. [2013]), and has additionally been found to be associated with total brain volume (Chauhan et al. [2015]). Note that the gene based analysis on IGAP data (Escott-Price et al. [2014]) identified some genes not found using this POLARIS approach. This could be because the POLARIS analysis focused on GERAD data rather than the IGAP data, and therefore does not have the same SNP coverage, or IGAP results could be influenced by other consortia.

Table IV: Gene-Wide Significant Genes from POLARIS Gene-based Analysis in GERAD Imputed Data Using a Gene Window (35kb Upstream and 10kb Downstream)

POLARIS

Chr Gene No. of SNPs Beta SE P-value

4 PPARGC1A 480 0.877 0.1851 2.2x10-6

8 SCARA3 (CLU) 240 0.526 0.1064 7.8x10-7

15 RORA 1813 0.334 0.0674 7.4x10-7

16 ZNF423 1056 0.551 0.1163 2.1x10-6

19 BCL3 88 0.377 0.0674 4.2x10-9

19 CBLC 50 0.605 0.1161 1.8x10-7

19 BCAM 71 0.556 0.0543 1.4x10-24

19 PVRL2 160 0.546 0.0299 9.4x10-75

19 TOMM40 108 0.500 0.0298 3.4x10-63

19 APOE 55 0.520 0.0315 4.4x10-61

19 APOC1 34 0.475 0.0315 1.5x10-51

19 APOC4-APOC2 62 0.615 0.0871 1.6x10-12

Figure 2: Manhattan Plot for the POLARIS Gene-Based Analysis in Imputed GERAD Data Using a Gene Window 35kb Upstream and 10kb Downstream

12 ↑ APOE

)

( RORA

0 CLU 1 6 g PPARGC1A ZNF423

0 1 2 3 4 5 6 7 8 9 11 13 15 18 21

Chromosome

The gene expression patterns in these novel genes were investigated using the BRAINEAC (Trabzuni et al. [2011]) database from the UK Brain Expression Consortium. For the PPARGC1A gene, the SNP rs67436520 has the best cis-expression quantitative trait loci (eQTL) p-value of 3.3x10-4, this is expressed in the hippocampus. The best cis-eQTL p-value in the RORA gene is 1.5x10-4, this is for SNP rs113223478 which is 78.5kb upstream of the gene, and is expressed in the substantia nigra. Finally, SNP rs2270396 has the best cis-eQTL p-value in the ZNF423 gene with a p-value of 3.0x10-5 and is expressed in the frontal cortex.

The gene-based analysis results from MAGMA-PCA and MAGMA-SUMMARY using a gene window identified genes which are in the APOE region (results are not shown). bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Conserved Regions GWAS data was interrogated for genes that are evolutionarily constrained, since such constraint indicates functional importance (Babarinde et al. [2016]). Genes from the gene-based analysis which are in the Exome Aggregation Consortium database (Lek et al. [2016]) and LoF intolerant were determined. Additionally, genes which overlap with conserved noncoding sequences were found (Babarinde et al. [2016]). It was then assessed whether there was enrichment for LoF intolerant genes or genes in conserved noncoding sequences using the POLARIS gene-based results in imputed data. There are 557 independent genes which do not overlap, for these genes, there is no enrichment for genes in conserved regions at either the nominal or gene-wide p-value threshold (OR=0.95, p=0.9052 and OR=4.19, p=0.3505 respectively). Similarly, no evidence of an enrichment of genes in conserved noncoding regions at either the nominal or gene-wide p-value threshold (OR=2.97, p=0.5586 and OR=31.57, p=1 respectively). Similar results were obtained for MAGMA derived p-values (results are not shown).

In summary, there is consistently no enrichment at the gene-wide p-value threshold for genes in either loss of function intolerant or conserved noncoding sequence regions, potentially due to the fact that AD is a post-reproductive disorder. Discussion A gene-based analysis was performed using the individual genotypes in the GERAD imputed data and the summary statistics from IGAP data excluding the GERAD subjects was used to inform the analysis. When no gene window is considered, POLARIS does not identify any novel genes, only genes on chromosome 19 which are likely influenced by the large effect of APOE. When a gene window was expanded around the gene, 35kb upstream and 10kb downstream, three novel genes were found from the POLARIS gene-based analysis. The gene window is likely to include transcriptional regulatory elements in the gene (Network and Consortium Pathway Analysis Subgroup of Psychiatric Genomics [2015]) and thus contain SNPs influencing gene expression.

Three novel genes were found to be associated with AD using the POLARIS method only. Gene-based analyses with MAGMA software identified only genome-wide significant genes in the APOE region. POLARIS determines a larger number of gene-wide significant genes compared to both the MAGMA approaches. This is consistent when the significance threshold is altered based on the number of genes from the analysis (0.05/no. genes). Supplementary Figures S1 and S2 show the gene p-value comparison between POLARIS and MAGMA-PCA and MAGMA-SUMM respectively; POLARIS generally has more significant p-values compared to both MAGMA approaches. This is likely due to the fact that MAGMA uses the GERAD data only whereas POLARIS additionally informs the analysis with the IGAPnoGERAD data. Thus, increasing power while maintaining the independence of the GERAD dataset. The novel genes are PPARGC1A, RORA and ZNF423, all of which have biological relevance to AD.

PPARGC1A (peroxisome proliferator-activated receptor gamma co-activator 1alpha) is a transcriptional bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

coactivator involved in a wide range of cellular and physiological functions. It is part of the PGC-1 family of transcriptional coactivators that mainly regulate mitochondrial biogenesis to in turn regulate the cellular energy metabolism (Luo et al. [2016]). The gene product, PGC-1, is an interacting partner of a wide range of nuclear receptors and transcription factors. It is associated with a wide-range of biological processes (Gene Ontology, http://www.ensembl.org), including response to a variety of cellular and external stimuli, cellular glucose homeostasis, circadian rhythm, regulation of neuron apoptosis, etc. Previous animal model work has shown that overexpression of hPGC-1 in APP23 mice improved spatial and recognition memory, along with significant reduction of Aβ deposition (Katsouri et al. [2016]). Furthermore, hPGC-1 overexpression also reduced the levels of proinflammatory cytokines and microglial activation (Nijland et al. [2014], Katsouri et al. [2016]). This suggests a direct link with recent genetic evidence of microglia-mediated innate immune response involvement in Alzheimer’s Disease (Sims et al. [2017]). In addition, an activation of PGC-1 by EKR and p38 inhibitors have been shown to improve spatial and learning memory in Aβ-injected rats (Ashabi et al. [2012]). PPARGC1A has also been implicated in the pathogenesis of other neurodegenerative disorders, namely Huntington’s and Parkinson’s diseases (Tsunemi et al. [2012]).

Retinoic acid receptor-related orphan receptor alpha (RORA) is a nuclear hormone receptor and is involved in a variety of functions, circadian rhythm, cholesterol metabolism, inflammation, etc (Jetten et al. [2009]). RORA binds to genomic regions of transcription start sites of more than 3,000 genes in human monocytic and endothelial cell lines (Gulec et al. [2017]). RORA and PPARGC1A are close biological partners, with PGC-1 stimulates the expression of a number of clock genes through the coactivation of the ROR family of orphan nuclear receptors (Liu et al. [2007]). RORA has been shown to be linked to other genes previously implicated in AD (Hu et al. [2017]) and has also been implicated in a large number of neuropsychiatric disorders, such as post-traumatic stress disorder (Miller et al. [2013]). Furthermore, RORA trans-activates Il-6 and is thought to be neuro-protective in astrocytes and anti- inflammatory in peripheral tissues (Journiac et al. [2009]). The two genes, RORA and PPARGC1A that we report here provide further evidence of the involvement of inflammation in the pathogenesis of Alzheimer’s disease.

Finally, ZNF423 is a nuclear protein that belongs to the Kruppel-like C2H2 zinc finger proteins. ZNF423 directs bone morphogenetic protein (BMP)-dependent signalling activity and aberrant forms impede B cell differentiation (Harder et al. [2013]). Furthermore, an increased gene-expression of ZNF423 has been associated in patients with systemic lupus erythematosus pointing to an impaired function of B cells in human mesenchymal stem cells (Feng et al. [2014]). ZNF423 resides in an AD-specific protein network (Hu et al. [2017]). ZNF423 is likely involved in DNA damage repair (Chaki et al, [2012]). Previously, it also has been shown that missense and LoF variants are likely pathogenic for abnormality of brain morphology, Joubert syndrome and Nephronophthisis with autosomal dominant or autosomal recessive inheritance (www.omim.org, https://www.ncbi.nlm.nih.gov/clinvar/). These disorders present bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

with a range of phenotypic characteristics, with the central nervous system being affected too (more specifically the cerebellar vermis). In nur12 mouse model (with introduced nonsense mutation in exon 4 of the mouse Zfp423 gene), Alcaraz et al. [2006] observed loss of the corpus callosum, reduction of hippocampus, and a malformation of the cerebellum reminiscent of patients with Dandy-Walker syndrome. Within the cerebellum, Zfp423 was observed to be expressed in both ventricular and external germinal zones. Loss of Zfp423 was also observed to lead to diminished proliferation by granule cell precursors in the external germinal layer and abnormal differentiation and migration of ventricular zone-derived neurons and Bergmann glia (Alcaraz et al. [2006]).

Genes determined from the gene-based analysis show no enrichment in conserved regions, in either evolutionary constrained LoF intolerant regions or in conserved noncoding sequences. This is expected in AD because it is a post-reproductive disorder. LoF highly penetrant rare variants in variation intolerant genes have been strongly linked to neurodevelopmental disorders with paediatric onset previously (Grozeva et al. [2015], Deciphering Developmental disorders study [2017]). Highly penetrant rare variants have been linked to familial AD with an early onset, but for the majority of individuals developing AD, this is not the case. In addition, rare copy number variants affecting haploinsufficient genes have been linked to SZ, but not AD (Grozeva et al. [2012], Chapman et al. [2013]). Therefore, it could be suggested that the mechanism of disease leading to AD, is different to mechanism leading to diseases with paediatric onset and are of neurodevelopmental origin. This is pointing to divergent biological mechanisms across the common and rare variant signals and between disorders polygenic in nature.

Supplementary Material

Figure S1: Gene –log10(p-value) Comparison Between POLARIS and MAGMA-PCA, with gene window

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Figure S2: Gene –log10(p-value) Comparison Between POLARIS and MAGMA-SUMMARY, with gene window

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POLARIS -log10(P) bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Figure S3: Gene –log10(p-value) Comparison Between MAGMA-PCA and MAGMA-SUMMARY, with gene window

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MAG-PCA -log10(P)

Appendix 1 Authors who contributed to the generation of original study data for GERAD, ADGC, CHARGE and EADI, but not to the current publication are included herein. Author affiliations can be found in the Supplementary material.

GERAD Consortium Magda Tsolaki1, David Craig2, Despoina Avramidou3, Antonia Germanou3, Maria Koutroumani3, Olymbia Gkatzima3, Harald Hampel5,92,93, Patrick G Kehoe6, Seth Love6, David C Rubinsztein7, Lutz Frölich8, Bernadette McGuinness9, Janet A Johnston9, Peter Passmore9, Dmitriy Drichel10, Amy Gerrish11, Nick C Fox11, Martin Rossor11, Jonathan M Schott11, Jason D Warren11, Jose Bras13,19,94, Rita Guerreiro13,19,94, Amit Kawalia14, Joseph T Hughes15, Yogen Patel15, Michelle K Lupton15,95, Petra Proitsi15,95, John Powell15,95, John S K Kauwe17, Michelangelo Mancuso18, Ubaldo Bonuccelli18, John Hardy19, James Uphill20, Elizabeth Fisher21, Carlo Masullo22, Hilkka Soininen23, Gina Bisceglio25, Li Ma25, Dennis W Dickson25, Neill R Graff- Radford25, Minerva M Carrasquillo25, Steven G Younkin25,96, Sandro Sorbi28,97, Makrina Daniilidou29, Angela Hodges30, Daniela Galimberti31, Elio Scarpini31, Martin Scherer32, Alfredo Ramirez34,14,65, Markus Leber34, Sabrina Pichler34, Manuel Mayhaus34, Wei Gu34, Matthias Riemenschneider34, Jens Wiltfang35,98,99, Reiner Heun36, Heike Kölsch36, Johannes Kornhuber38, Isabella Heuser39, Annette M Hartmann40, Ina Giegling40, Michael Hüll41, Simon Lovestone42, Carlos Cruchaga44,100, John Morris44,100, Kevin Mayo44, Thomas Feulner45, Rebecca Sussams46, Clive Holmes46, David Mann47, Stuart Pickering- Brown47, Nigel M Hooper47, Andrew McQuillin48, Gill Livingston48, Nicholas J Bass48, Rebecca Sims49, Maria Vronskaya49, Aura Frizatti49, Nandini Badarinarayan49, Taniesha Morgan49, Nicola Denning49, Thomas D Cushion49,91, Paul Hollingworth49, Lesley Jones49, Rachel Marshall49, Alun Meggy49, Georgina Menzies49, Ganna Leonenko49, Detelina Grozeva49, Michael C O’Donovan49, Michael J Owen49, Valentina Escott-Price49,91, Peter A Holmans49, Julie Williams49,91, Francesca Salani50, Paola Bossù50, Giancarlo Russo51, Wolfgang Maier52,36, Frank Jessen53,36,101, H-Erich Wichmann54,102,103, Kevin Morgan55, Alison M Goate56,100, Bruno Vellas57, Emma Vardy58, Susanne Moebus59, Karl-Heinz Jöckel59, Martin Dichgans61,104, Norman Klopp62, James Turton63, Jenny Lord63, Kristelle Brown63, Christopher Medway63, Markus M Nöthen64, Per Hoffmann65,105,106, Antonio Daniele66, Anthony Bayer67, John Gallacher67, Hendrik van den Bussche68, Carol Brayne69, Steffi Riedel-Heller70, John F Powell71, Ammar Al-Chalabi72, Christopher E Shaw72,107, Iwona Kloszewska73, Aoibhinn Lynch74,108, Brian Lawlor74,108, Michael Gill74,108, Eliecer Coto75, Victoria Alvarez75, Andrew B Singleton76, John Collinge77, Simon Mead77, Natalie Ryan77, Benedetta Nacmias78,109, Sara Ortega-Cubero79,110,111, Jacob Shofany80, Nerisa Banaj80, Eleonora Sacchinelli80, Gianfranco Spalletta80, Robert Clarke81, A David Smith82, Donald Warden82, Yoav Ben-Shlomo83, Chiara Cupidi84, Raffaele Giovanni Maletta84, Amalia Cecilia Bruni84, Maura Gallo84, Denise Harold85, Roberta Cecchetti86, Patrizia Mecocci86, Pau Pastor86, Virginia Boccardi86, Nick Warner88, Gordon Wilcock89, Panagiotis Deloukas90, Rhian Gwilliam90, Rachel Raybould91, Chris Corcoran92, JoAnn Tschanz92, Ron Munger92, Valentina Ciullo80 bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

13rd Department of Neurology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece, 2Ageing Group, Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, UK, 3Aristotle University of Thessaloniki, Despere 3, Thessaloniki, 54621, Greece, 5AXA Research Fund & UPMC Chair, Paris, France, 6Bristol Medical School, University of Bristol, Southmead Hospital, Bristol, UK, 7Cambridge Institute for Medical Research and UK Dementia Research Institute, University of Cambridge, Cambridge, UK, 8Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany, 9Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queens University, Belfast, UK, 10Cologne Center for Genomics, University of Cologne, Cologne, Germany, 11Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK, 13Dementia Research Institute at UCL, 14Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany, 15Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London UK, 17Department of Biology, Brigham Young University, Provo, Utah, USA, 18Department of Experimental and Clinical Medicine, Neurological Institute, University of Pisa, Italy, 19Department of Molecular Neuroscience, UCL, Institute of Neurology, London, UK, 20Department of Neurodegenerative Disease, MRC Prion Unit, UCL Institute of Neurology, London, UK, 21Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK, 22Department of Neurology, Catholic University of Rome, Rome, Italy, 23Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland, 25Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, 32224, USA, 28Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Italy Viale Pieraccini 6, 50139 Florence, Italy, 29Department of Neuroscience, Uppsala University, Uppsala, Sweden, 30Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London UK, 31Department of Pathophysiology and Transplantation, University of Milan, Fondazione Ca’ Granda, IRCCS Ospedale Policlinico, Milan, Italy, 32Department of Primary Medical Care, University Medical Centre Hamburg-Eppendorf, 20246 Hamburg, Germany, 34Department of Psychiatry and Psychotherapy, University Hospital, Saarland, Germany, 35Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August- University, von-Siebold-Strasse 5, 37075 Göttingen, 36Department of Psychiatry and Psychotherapy, University of Bonn, 53127, Bonn, Germany, 38Department of Psychiatry and Psychotherapy, University of Erlangen-Nuremberg, Germany, 39Department of Psychiatry, Charité Berlin, Germany, 40Department of Psychiatry, Martin-Luther-University Halle-Wittenberg, Halle, Germany, 41Department of Psychiatry, University of Freiburg, Freiburg, Germany (M.H.), 42Department of Psychiatry, University of Oxford, Oxford, UK, 44Departments of Psychiatry, Neurology and Genetics, Washington University School of Medicine, St Louis, MO 63110, US, 45Dept. Of Psychiatry, University Hospital, Saarland, 46Division of Clinical Neurosciences, School of Medicine, University of Southampton, Southampton, UK, 47Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester M13 9PT, UK, 48Division of Psychiatry, University College London, UK, 49Division of Psychological Medicine and bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Clinial Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK, 50Experimental Neuropsychobiology Laboratory, IRCCS Santa Lucia Foundation, Department of Clinical and Behavioral Neurology, Rome, Italy, 51Functional Genomics Center Zurich, ETH/University of Zurich, 52German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany, 53German Center for Neurodegenerative Diseases (DZNE), 53175, Bonn, Germany, 54Helmholtz Center Munich, Institute of Epidemiology, Neuherberg, 55Human Genetics, School of Life Sciences, Life Sciences Building A27, University Park, University of Nottingham, Nottingham, NG7 2RD, United Kingdom, 56Icahn School of Medicine at Mount Sinai, New York, NY, USA, 57INSERM U 558, University of Toulouse, Toulouse, France, 58Institute for Ageing and Health, Newcastle University, Biomedical Research Building, Campus for Ageing and Vitality, Newcastle upon Tyne, 59Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Hufelandstr, 55, D-45147 Essen, Germany, 61Institute for Stroke and Dementia Research, Klinikum der Universität München, Munich, Germany, 62Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany, 63Institute of Genetics, Queens Medical Centre, University of Nottingham, Nottingham, UK, 64Institute of Human Genetics, Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany, 65Institute of Human Genetics, University of Bonn, Bonn, Germany, 66Institute of Neurology, Catholic University of Sacred Hearth, Rome, Italy, 67Institute of Primary Care and Public Health, Cardiff University, Neuadd Meirionnydd, University Hospital of Wales, Heath Park, Cardiff UK, 68Institute of Primary Medical Care, University Medical Center Hamburg- Eppendorf, Germany, 69Institute of Public Health, University of Cambridge, Cambridge, UK, 70Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, 04103 Leipzig, Germany, 71King's College London, Institute of Psychiatry, Department of Neuroscience, De Crespigny Park, Denmark Hill, London SE5, 72Kings College London, Institute of Psychiatry, Psychology and Neuroscience, UK, 73Medical University of Lodz, Lodz, Poland, 74Mercer's Institute for Research on Ageing, St James' Hospital, Dublin 8, 75Molecular Genetics Lab-Hospital Univ Central Asturias, Oviedo, Spain, 33011- Oviedo-Spain, 76Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA, 77MRC Prion Unit at UCL, Institute of Prion Diseases, London, 78NEUROFARBA (Department of Neuroscience, Psychology, Drug Research and Child Health), University of Florence, Florence, Italy, 79Neurogenetics Laboratory, Division of Neurosciences, Centre for Applied Medical Research, University of Navarra School of Medicine, Pamplona, Spain, 80Neuropsychiatry Laboratory, IRCCS Santa Lucia Foundation, Department of Clinical and Behavioral Neurology, Rome, Italy, 81Oxford Healthy Aging Project (OHAP), Clinical Trial Service Unit, University of Oxford, Oxford, UK, 82Oxford Project to Investigate Memory and Ageing (OPTIMA), University of Oxford, Level 4, John Radcliffe Hospital, Oxford OX3 9DU, UK, 83Population Health Sciences, Bristol Medical School, University of Bristol, 84Regional Neurogenetic Centre (CRN), ASP Catanzaro, Lamezia Terme, Italy, 85School of Biotechnology, Dublin City University, Dublin 9, Ireland, 86Section of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy, 88Somerset Partnership NHS Trust, Somerset, UK, 89The Oxford Project To Investigate Memory and Ageing, Nuffield Department of bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Clinical Neurosciences, University of Oxford, West Wing, John Radcliffe Hospital, Oxford. OX3 9DJ, 90The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK, 91UKDRI Cardiff, Cardiff University, Cardiff, UK, 92Utah State University, Logan, Utah, USA, 92Sorbonne Universités, Université Pierre et Marie Curie, Paris, 93Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A) & Institut du Cerveau et de la Moelle épinière (ICM), Département de Neurologie, Hôpital de la Pitié- Salpêtrière, Paris, France, 94Department of Medical Sciences, Institute of Biomedicine iBiMED, University of Aveiro, 3810-193 Aveiro, Portugal, 95Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia, 96Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA, 97IRCCS Don Gnocchi , Florence, Italy, 98German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany, 99Institute for Research in Biomedicine (iBiMED), Medical Sciences Department, University of Aveiro, Aveiro, Portugal, 100Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University School of Medicine, St. Louis, Missouri, USA, 101Department of Psychiatry and Psychotherapy, University of Cologne, 50937 Cologne, Germany, 102Ludwig- Maximilians University Chair of Epidemiology, Munich, Germany, 103Joint Biobank Munich and KORA Biobank, 104German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, 80336, Germany, 105Department of Genomics, Life & Brain Center, University of Bonn, 53127, Bonn, Germany; 21, 106Division of Medical Genetics, University Hospital and Department of Biomedicine, University of Basel, CH-4058, Basel, Switzerland, 107UK Dementia Research Institute at King's College London, UK, 108James Hospital and Trinity College, Dublin, Ireland, 109Centro di Ricerca, Trasferimento e Alta Formazione DENOTHE, University of Florence, Florence, Italy, 110CIBERNED, Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain, 111Department of Neurology, Complejo Asistencial Universitario de Palencia, Spain

ADGC Consortium Regina M. Carney1, Deborah C. Mash2, Marilyn S. Albert3, Roger L. Albin4,5, Liana G. Apostolova6, Steven E. Arnold8, Clinton T. Baldwin8, Michael M. Barmada9, Lisa L. Barnes10,11, Thomas G. Beach12, Eileen H. Bigio13, Thomas D. Bird14, Bradley F. Boeve15, James D. Bowen16, Adam Boxer17, James R. Burk18, Nigel J. Cairns19, Chuanhai Cao20, Chris S. Carlson21, Steven L. Carroll22, Lori B. Chibnik23,24, Helena C. Chui25, David G. Clark26, Jason Corneveaux27, David G. Cribbs28, Charles DeCarli29, Steven T. DeKosky30, F. Yesim Demirci9, Malcolm Dick31, Dennis W. Dickson32, Ranjan Duara33, Nilufer Ertekin-Taner32,34, Kenneth B. Fallon22, Martin R. Farlow35, Steven Ferris36, Matthew P. Frosch37, Douglas R. Galasko38, Mary Ganguli39, Marla Gearing40,41, Daniel H. Geschwind42, Bernardino Ghetti43, Sid Gilman4 , Jonathan D. Glass44, Robert C. Green45, John H. Growdon46, Ronald L. Hamilton47, Chiao-Feng Lin48, Lindy E. Harrell26, Elizabeth Head49, Lawrence S. Honig50, Christine M. Hulette51, Bradley T. Hyman46, Gail P. Jarvik52,53, Gregory A. Jicha54, Lee-Way Jin55, Anna Karydas17, John S. K. Kauwe56, Jeffrey A. Kaye57,58, Ronald Kim59, Edward H. Koo38, Neil W. Kowall60,61, Joel H. Kramer62, Patricia Kramer57,63, Frank M. LaFerla64, James J. Lah44, James B. Leverenz65, Allan I. Levey44, Ge Li66, Andrew P. Lieberman67, Constantine G. Lyketsos68, Wendy J. Mack69, Daniel C. Marson26, Frank Martiniuk70, Eliezer Masliah38,71, Wayne C. McCormick72, Susan M. bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

McCurry73, Andrew N. McDavid21, Ann C. McKee60,61, Marsel Mesulam74, Bruce L. Miller17, Carol A. Miller75, Brian Kunkle76, Joshua W. Miller55, John C. Morris19,77, Jill R. Murrell43,78, John M. Olichney29, Vernon S. Pankratz80, Joseph E. Parisi81,82, Elaine Peskind66, Tricia A. Thornton-Wells83,15, Ronald C. Petersen1583, Aimee Pierce28, Wayne W. Poon31, Huntington Potter84, Joseph F. Quinn57, Ashok Raj84, Murray Raskind66, Eric M. Reiman27,85,86, Barry Reisberg36,87, John M. Ringman6 , Erik D. Roberson26,48, Howard J. Rosen17, Roger N. Rosenberg88, Mary Sano89, Andrew J. Saykin43,90, Julie A. Schneider10,91, Lon S. Schneider6,92, William W. Seeley17, Amanda G. Smith84, Joshua A. Sonnen65, Salvatore Spina43, Robert A. Stern60, Rudolph E. Tanzi46, John Q. Trojanowski93, Juan C. Troncoso94, Vivianna M. Van Deerlin93, Linda J. Van Eldik95, Harry V. Vinters6,96, Jean Paul Vonsattel97, Sandra Weintraub74, Robert Green98, Kathleen A. Welsh-Bohmer18,99, Jennifer Williamson50, Randall L. Woltjer100, Chang-En Yu72, Robert Barber101, Adam C. Naj102,103, Gyungah Jun104,105,106, Gary W. Beecham1,107, Badri N. Vardarajan104, Otto Valladares48, Christiane Reitz108,109, Joseph D. Buxbaum110,111,112, Clinton Baldwin104, Najaf Amin113, Philip L. De Jager114,115, Denis Evans116, Matthew J. Huentelman117, M. Ilyas Kamboh118,119, Amanda J. Myers120, Ekaterina Rogaeva121, Peter St George-Hyslop121,122, Lei Yu123, John R. Gilbert1,107, Hakon Hakonarson124, Kara L. Hamilton-Nelson1 , Kelley M. Faber125, Laura B. Cantwell48, Deborah Blacker126,127, David A. Bennett123,128, Thomas J. Montine129, Tatiana M. Foroud125, Walter A. Kukull130, Kathryn L. Lunetta106, John S. K. Kauwe131, Eric Boerwinkle132,133, Eden R. Martin1,107, Li-San Wang48.

1The John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, 33124, USA 2Department of Neurology, University of Miami, Miami, FL, 33124, USA 3Department of Neurology, Johns Hopkins University, Baltimore, MD, 21218, USA 4Department of Neurology, University of Michigan, Ann Arbor, MI, 48109, USA 5Geriatric Research, Education and Clinical Center (GRECC), VA Ann Arbor Healthcare System (VAAAHS), Ann Arbor, MI, 48109, USA 6Department of Neurology, University of California Los Angeles, Los Angeles, CA, 94607, USA 7Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA 8Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, 02215, USA 9Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, 15213, USA 10Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA 11Department of Behavioral Sciences, Rush University Medical Center, Chicago, IL, 60612, USA 12Civil Laboratory for Neuropathology, Banner Sun Health Research Institute, Phoenix, AZ, 85351, USA 13Department of Pathology, Northwestern University, Chicago, IL, 60208, USA 14Department of Neurology, University of Washington, Seattle, WA, 98195, USA 15Department of Neurology, Mayo Clinic, Rochester, MN, 55902, USA 16Swedish Medical Center, Seattle, WA, 98195, USA 17Department of Neurology, University of California San Francisco, San Francisco, CA, 94122, USA 18Department of Medicine, Duke University, Durham, NC, 27710, USA 19Department of Pathology and Immunology, Washington University, St. Louis, MO, 63130, USA 20USF Health Byrd Alzheimer's Institute, University of South Florida, Tampa, CA, 33620, USA 21Fred Hutchinson Cancer Research Center, Seattle, WA, 98195, USA 22Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA 23Program in Translational NeuroPsychiatric bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Genomics, Institute for the Neurosciences, Department of Neurology & Psychiatry, Bringham and Women's Hospital, Harvard Medical School, Boston, MA, 02215, USA 24Program in Medical and Population Genetics, Broad Institute, Boston, MA, 02215, USA 25Department of Neurology, University of Southern California, Los Angeles, CA, 94607, USA 26Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA 27Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ, 85004, USA 28Department of Neurology, University of California Irvine, Irvine, CA, 92617, USA 29Department of Neurology, University of California Davis, Sacramento, CA, 95616, USA 30University of Virginia School of Medicine, Charlottesville, VA, 22903, USA 31Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine, CA, 92617, USA 32Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 55902, USA 33Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, 10029, USA 34Department of Neurology, Mayo Clinic, Jacksonville, FL, 55902, USA 35Department of Neurology, Indiana University , Indianapolis, IN, 46202, USA 36Department of Psychiatry, New York University, New York, NY, 10027, USA 37C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Charlestown, MA, 02114, USA 38Department of Neurosciences, University of California San Diego, La Jolla, CA, 92093, USA 39Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA 40Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, 30329, USA 41Emory Alzheimer's Disease Center, Emory University, Atlanta, GA, 30329, USA 42Neurogenetics Program, University of California Los Angeles, Los Angeles, CA, 94607, USA 43Department of Pathology and Laboratory Medicine, Indiana University, Indianapolis, IN, 46202, USA 44Department of Neurology, Emory University, Atlanta, GA, 30329, USA 45Division of Genetics, Department of Medicine and Partners Center for Personalized Genetic Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02215, USA 46Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, 02215, USA 47Department of Pathology (Neuropathology), University of Pittsburgh, Pittsburgh, PA, 15213, USA 48Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA 49Sanders-Brown Center on Aging, Department of Molecular and Biomedical Pharmacology, University of Kentucky, Lexington, KY, 40506, USA 50Taub Institute on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University, New York, NY, 10027, USA 51Department of Pathology, Duke University, Durham, NC, 27710, USA 52Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA 53Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, 98195, USA 54Sanders-Brown Center on Aging, Department Neurology, University of Kentucky, Lexington, KY, 40506, USA 55Department of Pathology and Laboratory Medicine, University of California Davis, Sacramento, CA, 95616, USA 56Department of Biology, Brigham Young University, Provo, UT 02215, USA 57Department of Neurology, Oregon Health & Science University, Portland, OR, 97239, USA 58Department of Neurology, Portland Veterans Affairs Medical Center, Portland, OR, 97239, USA 59Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine, CA, 92617, USA 60Department of Neurology, Boston University School of Medicine, Boston, MA, 02215, USA bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

61Department of Pathology, Boston University School of Medicine, Boston, MA, 02215, USA 62Department of Neuropsychology, University of California San Francisco, San Francisco, CA, 94122, USA 63Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, 97239, USA 64Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, 92617, USA 65Department of Pathology, University of Washington, Seattle, WA, 98195, USA 66Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, 98195, USA 67Department of Pathology, University of Michigan, Ann Arbor, MI, 48109, USA 68Department of Psychiatry, Johns Hopkins University, Baltimore, MD, 21218, USA 69Department of Preventive Medicine, University of Southern California, Los Angeles, CA, 94607, USA 70Department of Medicine - Pulmonary, New York University, New York, NY, 10027, USA 71Department of Pathology, University of California San Diego, La Jolla, CA, 92093, USA 72Department of Medicine, University of Washington, Seattle, WA, 98195, USA 73School of Nursing Northwest Research Group on Aging, University of Washington, Seattle, WA, 98195, USA 74Cognitive Neurology and Alzheimer's Disease Center, Northwestern University, Chicago, IL, 60208, USA 75Department of Pathology, University of Southern California, Los Angeles, CA, 94607, USA 76Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA 77Department of Neurology, Washington University, St. Louis, MO, 98101, USA 78Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, 46202, USA 80Department of Biostatistics, Mayo Clinic, Rochester, MN, 55902, USA 81Department of Anatomic Pathology, Mayo Clinic, Mayo Clinic, Rochester, MN, 55902, USA 82Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55902, USA 83Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37212, USA 84USF Health Byrd Alzheimer's Institute, University of South Florida, Tampa, FL, 33613, USA 85Arizona Alzheimer’s Consortium, Department of Psychiatry, University of Arizona, Phoenix, AZ, 85004, USA 86Banner Alzheimer's Institute, Phoenix, AZ, 85004, USA 87Alzheimer's Disease Center, New York University, New York, NY, 10027, USA 88Department of Neurology, University of Texas Southwestern, Dallas, TX, 75390, USA 89Department of Psychiatry, Mount Sinai School of Medicine, New York, NY, 10027, USA 90Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, 46202, USA 91Department of Pathology (Neuropathology), Rush University Medical Center, Chicago, IL, 60208, USA 92Department of Psychiatry, University of Southern California, Los Angeles, CA, 94607, USA 93Department of Pathology and Laboratory Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA 94Department of Pathology, Johns Hopkins University, Baltimore, MD, 21218, USA 95Sanders-Brown Center on Aging, Department of Anatomy and Neurobiology, University of Kentucky, Lexington, KY, 40506, USA 96Department of Pathology & Laboratory Medicine, University of California Los Angeles, Los Angeles, CA, 94607, USA 97Taub Institute on Alzheimer's Disease and the Aging Brain, Department of Pathology, Columbia University, New York, NY, 10027, USA 98Division of Genetics, Department of Medicine and Partners Center for Personalized Genetic Medicine, Brigham and Women's Hospital and Harvard Medical School, USA. 99Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC, 27710, USA 100Department of bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Pathology, Oregon Health & Science University, Portland, OR, 97239, USA 101Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, 76102, USA 102Department of Biostatistics Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA 103Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA 104Department of Medicine (Biomedical Genetics), Boston University School of Public Health, Boston, MA, 02218, USA 105Department of Ophthalmology, Boston University School of Public Health, Boston, MA, 02215, USA 106Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA 107Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, 33124, USA 108Taub Institute on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University New York, NY, 10027, USA 109Gertrude H. Sergievsky Center, Department of Neurology, Columbia University, New York, NY, 10027, USA 110Department of Neuroscience, Mount Sinai School of Medicine, New York, NY 10027, USA 111Department of Psychiatry, Mount Sinai School of Medicine, New York, NY 10027, USA 112Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, NY 10027, USA 113Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, 3015 CE the Netherlands 114Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Department of Neurology & Psychiatry, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02215 USA 115Program in Medical and Population Genetics, Broad Institute, Boston, MA 02215 USA 116Rush Institute for Healthy Aging, Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA 117Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA 118Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15213, USA 119Alzheimer's Disease Research Center, University of Pittsburgh, Pittsburgh, PA 15213, USA 120Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, FL 33124, USA 121Tanz Centre for Research in Neurodegenerative Disease, University of Toronto, Toronto, ON M5S 1A1, Canada 122Cambridge Institute for Medical Research and Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 1TN, UK 123Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA 124Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA 125Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN 46202, USA 126Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA 127Department of Psychiatry, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02115, USA 128Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA 129Department of Pathology, University of Washington, Seattle, WA 98195, USA 130Department of Epidemiology, University of Washington, Seattle, WA 98195, USA 131Department of Biology, Brigham Young University, Provo, UT, 84602, USA 132Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA 133Human Genetics Center and Div. of Epidemiology, University of Texas Health Sciences Center at Houston, Houston, TX 77030, USA bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

CHARGE Consortium Rhoda Au1 , Philip A. Wolf1 , Alexa Beiser2 , Stephanie Debette1,3, Qiong Yang2 , Galit Weinstein1, Andrew D. Johnson4, Jing Wang2, Andre G. Uiterlinden5,6,7, Fernando Rivadeneira5, Peter J. Koudstaal8, William T. Longstreth Jr9,10,11, James T. Becker12, Lewis H. Kuller13, Thomas Lumley14, Kenneth Rice15, Melissa Garcia16, Thor Aspelund17, Josef J. M. Marksteiner18, Peter Dal-Bianco19, Anna Maria Töglhofer20, Paul Freudenberger20, Gerhard Ransmayr21, Thomas Benke22, Anna M. Toeglhofer20, Jan Bressler23, Monique M. B. Breteler24, Myriam Fornage25, Reinhold Schmidt26, Reposo Ramírez-Lorca27, Antonio González- Perez27, Carla A. Ibrahim-Verbaas28, Anita L. DeStefano29, Tamara B. Harris30, Albert V. Smith31,32, M. Arfan Ikram33,34, Helena Schmidt20, Seung-Hoan Choi29, Annette L. Fitzpatrick30,35, Paul K. Crane36, Vilmundur Gudnason31,32, Oscar L. Lopez37, Francisco J. Morón27, Gudny Eiriksdottir32, Eric B. Larson36,38, Debby W. Tsuang39, Duane Beekly40, Palmi V. Jonsson31,41, Thomas H. Mosley Jr42, Renee FAG de Bruijn43, Jerome I. Rotter44, Michael A. Nalls45, Albert Hofman33,34, Bruce M. Psaty30,46.

1Department of Neurology, Boston University School of Medicine, Boston, MA2118, USA 2Department of Biostatistics, Boston University School of Public Health, Boston, MA2118, USA 3UMR744 Inserm, Lille, France 4NHLBI Center for Cardiovascular Genomics, the Framingham Study, Framingham, MA1702, USA 5Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, 3000 CA, the Netherlands (Uiterlinden) 6Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands (Uiterlinden) 7Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands(Uiterlinden) 8Department of Neurology, Erasmus MC University Medical Center, Rotterdam 3000 CA, the Netherlands 9Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA 10Department of Epidemiology, University of Washington, Seattle, WA 98101, USA 11Group Health Research Institute, Group Health Cooperative, Seattle, WA 98101, USA 12The Departments of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA 13Departments of Medicine and Epidemiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA 14Department of Statistics, University of Auckland, Auckland, New Zealand. 15Department of Biostatistics, University of Washington, School of Medicine, Seattle, WA 98101, USA 16Laboratory of Epidemiology, Demography and Biometry, National Institute on Aging, Bethesda, MD, 20892, USA 17The Icelandic Heart Association, Landspitali-University Hospital, Reykjavik, Iceland 18Department of Psychiatry and Psychotherapy, General Hospital, Hall, 6060, Austria 19Department of Neurology, Medical University of Vienna, Vienna, 1090, Austria 20Institute for Molecular Biology and Biochemistry, Medical University of Graz, Graz, 8010, Austria 21Department of Neurology and Psychiatry,General Hospital Linz, Austria, Linz, 4020, Austria 22Clinic of Neurology, Medical University Innsbruck, Innsbruck, 6020, Austria 23School of Public Health, University of Texas Health Sciences Center at Houston, Houston, TX 77030, USA 24German Center for Neurodegenerative diseases (DZNE), Bonn, 53175, Germany 25Institute of Molecular Medicine and School of Public Health Division of Epidemiology Human Genetics and Environmental Sciences, University of Texas Health Sciences Center at Houston, Houston, TX 77030, USA 26Department bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

of Neurology, Medical University Graz, Graz, Austria 27Departamento de Genómica Estructural . Neocodex, Sevilla, 8029, Spain 28Department of Epidemiology, Clinical Genetics and Neurology, Erasmus MC University Medical Center, Rotterdam, 3015 CE, the Netherlands 29Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA 30Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA 31University of Iceland, Faculty of Medicine, Reykjavik, Iceland 32Icelandic Heart Association, Kopavogur, Iceland 33Departments of Epidemiology, Neurology and Radiology, Erasmus MC University Medical Center, Rotterdam, 3015 CE, the Netherlands 34Netherlands Consortium for Healthy Aging, Leiden, The Netherlands 35Department of Epidemiology and Global Health, University of Washington, Seattle, WA 98101, USA 36Department of Medicine, University of Washington, Seattle, WA 98195, USA 37Departments of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213 USA 38Group Health Research Institute, Group Health, Seattle, WA 98195, USA 39Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA 40National Alzheimer's Coordinating Center, University of Washington, Seattle, WA 98195, USA 41Landspitali University Hospital, Reykjavik, Iceland 42Department of Medicine (Geriatrics), University of Mississippi Medical Center, Jackson, MS 39216 USA 43Departments of Neurology and Epidemiology, Erasmus MC University Medical Center, Rotterdam, 3015 CE, the Netherlands 44Medical Genetics Institute, Cedars- Sinai Medical Center, Los Angeles, CA 90048, USA 45Laboratory of Neurogenetics, Intramural Research Program, National Institute on Aging, Bethesda, MD 20892, USA 46Group Health Research Institute, Group Health Cooperative, Seattle, WA. 98101, USA

EADI Consortium Benjamin Grenier-Boley1,2,3, Florence Pasquier2,4, Vincent Deramecourt2,4, Nathalie Fiévet1,3, Diana Zelenika5 , Yoichiro Kamatani6 , Marie-Thérèse Bihoreau5 , Mark Lathrop5,6,7, Olivier Hanon8 , Dominique Campion9 , Claudine Berr10, Luc Letenneur11, Kristel Sleegers12,13, Lina Keller14, Pascale Barberger- Gateau11, Carole Dufouil11, David Wallon9 , Jordi Clarimon15,16, Alberti Lleo15,16, Paola Bossù17, Gianfranco Spalletta17, Sandro Sorbi18,19, Florentino Sanchez Garcia20, Maria Candida Deniz Naranjo20, Paolo Bosco21, Daniela Galimberti22, Michelangelo Mancuso23, Patrizia Mecocci24, Maria Del Zompo25, Alberto Pilotto26, Maria Bullido27,28,29, Francesco Panza30, Paolo Caffarra31,32, Benedetta Nacmias18,19, Lars Lannfelt33, Martin Ingelsson33, Victoria Alvarez34, Cristina Razquin35, Pau Pastor35,36, Ignacio Mateo37, Eliecer Coto34, Onofre Combarros37, Hilkka Soininen38,39, Laura Fratiglioni14,40, Karolien Bettens12,13, Alexis Brice41,42, Didier Hannequin9 , Karen Ritchie10,43, Mikko Hiltunen38,39, Jean-François Dartigues11,44, Christophe Tzourio45, Caroline Graff40,46, Annick Alpérovitch47, Anne Boland5 , Marc Delépine5 , Bruno Dubois48, Emmanuelle Duron49, Jacques Epelbaum50, Caroline Van Cauwenberghe12,51, Sebastiaan Engelborghs51,52, Rik Vandenberghe53,54, Peter P. De Deyn51,52, Raffaele Ferri55, Carmelo Romano55, Carlo Caltagirone56, Maria Donata Orfei56, Antonio Ciaramella56, Elio Scarpini57,58, Chiara Fenoglio57,58, Gabriele Siciliano23, Ubaldo Bonuccelli23, Silvia Bagnoli19,59, Laura Bracco19,59, Valentina Bessi19,59, Roberta Cecchetti24, Patrizia Bastiani24, Alessio Squassina60, Davide Seripa61, Ana Frank-García28,29,62, Isabel Sastre,28,29,63, Rafael bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Blesa16,64, Daniel Alcolea16,64, Marc Suárez-Calvet16,64, Pascual Sánchez-Juan37, Carmen Munõz Fernandez65, Yolanda Aladro Benito65, Caroline Graff68,67, Laura Fratiglioni68, Håkan Thonberg66,67, Charlotte Forsell67, Lena Lilius67, Anne KinhultStåhlbom66,67, Vilmantas Giedraitis33, Lena Kilander33, Rose Marie Brundin33, Letizia Concari69,70, Seppo Helisalmi39,71, Anne Maria Koivisto39,71, Annakaisa Haapasalo39,71, Vincenzo Solfrizzi72, Vincenza Frisardi73, Jurg Ott74, Christine Van Broeckhoven12,13.

1Inserm, U744, Lille, 59000, France 2Université Lille2, Lille, 59000, France 3Institut Pasteur de Lille, Lille, 59000, France 4CNR-MAJ, Centre Hospitalier Régional Universitaire de Lille, Lille, 59000, France 5Centre National de Genotypage, Institut Genomique, Commissariat à l'énergie Atomique, Evry,France 6Fondation Jean Dausset, CEPH, Paris, France 7McGill University and Génome Québec Innovation Centre, Montreal, Canada 8University Paris Descartes, Sorbonne Paris V; Broca Hospital, Geriatrics department; Paris, France 9CNR-MAJ; Inserm, U1079; Rouen University Hospital; 76031 France, Rouen, France 10Inserm, U1061; Faculty of Medicine; Hôpital La Colombière; Montpellier, France 11Inserm, U897; Victor Segalen University; F-33076, Bordeaux, France 12Neurodegenerative Brain Diseases Group, Department of Molecular Genetics, VIB, Antwerp, Belgium 13Department of Molecular Genetics, VIB, Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium 14Aging Reasearch Center, Dept Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden 15Neurology Department. IIB Sant Pau. Sant Pau Hospital. Universitat Autònoma de Barcelona, Barcelona, Spain. 16Center for Networker Biomedical Research in Neurodegenerative Diseases (CIBERNED), Barcelona, Spain. 17Clinical and Behavioral Neurology, Fondazione Santa Lucia, Roma, Italy 18Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy 19Centro di Ricerca, Trasferimento e Alta Formazione DENOTHE, University of Florence, Florence, Italy 20Department of Immunology, Hospital Universitario Dr. Negrin, Las Palmas de Gran Canaria, Spain 21IRCCS Associazione Oasi Maria SS, Troina, Italy 22University of Milan, Fondazione Cà Granda, IRCCS Ospedale Policlinico, Milan, Italy 23Neurological Clinic, University of Pisa, Italy 24Section of Gerontology and Geriatrics, Department Medicine, University of Perugia, Perugia, Italy 25Section of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy 26Gerontology and Geriatrics Research Laboratory, I.R.C.C.S. Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy 27Centro de Biología Molecular Severo Ochoa (CSIC-UAM); Madrid, Spain 28Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain 29Instituto de Investigación Sanitaria “Hospital la Paz” (IdIPaz), Madrid, Spain 30Departement of Geriatrics, Center for Aging Brain, University of Bari, Bari, Italy 31Department of Neuroscience-University of Parma, Parma, Italy 32Center for Cognitive Disorders AUSL, Parma, Italy 33Dept. of Public Health/Geriatrics, Uppsala University, Uppsala, Sweden 34Genetica molecular-Huca-Oviedo, Oviedo, Spain 35Neurogenetics Laboratory, Division of Neurosciences, Center for Applied Medical Research, University of Navarra School of Medicine, Pamplona, Spain 36CIBERNED, Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Spain 37Neurology Service and CIBERNED, "Marqués bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

de Valdecilla" University Hospital (University of Cantabria and IFIMAV), Santander, Spain 38Institute of Clinical Medicine - Neurology, University of Eastern Finland, Kuopio, 70211 Finland 39Department of Neurology, Kuopio University Hospital, FIN-70211 Kuopio, Finland 40Dept Geriatric Medicine, Genetics Unit, Karolinska University Hospital Huddinge, S-14186 Stockholm 41INSERM UMR_S975-CNRS UMR 7225, Université Pierre et Marie Curie, Centre de recherche de l'Institut du Cerveau et de la Moëlle épinière-CRICM, Hôpital de la Salpêtrière, Paris France 42AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France 43Imperial College, London 44Centre de Mémoire de Ressources et de Recherche de Bordeaux, CHU de Bordeaux, Bordeaux, France 45Inserm, U708; Victor Segalen University; F-33076, Bordeaux, France 46Karolinska Institutet, Dept Neurobiology, Care Sciences and Society, KIADRC, Novum floor 5, S14186 Stockholm, Sweden 47Inserm U708, Victor Segalen University, F-33076, Bordeaux, France 48IM2A - CRicm-UMRS975, AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France 49CMRR Paris Sud Ile-de-France, service de gériatrie, Hôpital Broca, 54-56 rue Pascal, 75013 Paris 50UMR 894 Inserm, Psychiatry and Neurosciences Center, Paris, France 51Institute Born-Bunge, University of Antwerp, Antwerp, Belgium 52Department of Neurology and Memory Clinic, Hospital Network Antwerp, Antwerp, Belgium 53Laboratory for Cognitive Neurology, Department of Neurology, University of Leuven, Leuven, Belgium 54Department of Neurology and Memory Clinic, University Hospitals Leuven Gasthuisberg, Leuven, Belgium 55IRCCS Associazione Oasi Maria SS, Troina, Italy 56Clinical and Behavioral Neurology, Fondazione Santa Lucia, Roma ,Italy 57University of Milan, Milan, Italy 58Fondazione Cà Granda, IRCCS Ospedale Policlinico, Milan, Italy 59Department of Neurological and Psychiatric Sciences, University of Florence, Florence, Italy 60Section of Neuroscience and Clinical Pharmacology, Department of Biomedical Science, University of Cagliari, Cagliari, Italy 61Gerontology and Geriatrics Research Laboratory, I.R.C.C.S. Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy 62Neurology Service; Hospital Universitario La Paz (UAM), Madrid, Spain 63Centro de Biología Molecular Severo Ochoa (CSIC-UAM), Madrid, Spain 64Neurology Department. IIB Sant Pau. Sant Pau Hospital. Universitat Autònoma de Barcelona. Barcelona, Spain. 65Department of Neurology, Hospital Universitario Dr. Negrin, Las Palmas de Gran Canaria, Spain 66Dept Geriatric Medicine, Genetics Unit, Karolinska University Hospital Huddinge, S-14186 Stockholm, Sweden 67Karolinska Institutet, Dept NVS, Center for Alzheimer Research, Division for Neurogeriatrics, 141 57 Huddinge, Sweden. 68Aging Reasearch Center, Dept Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden 69Department of Neuroscience-University of Parma-Italy, Parma, Italy 70Center for Cognitive Disorders AUSL, Parma, Italy 71Institute of Clinical Medicine - Neurology, University of Eastern Finland, FIN-70211, Kuopio, Finland 72Department of Geriatrics, Center for Aging Brain ,University of Bari, Bari, Italy 73Department of Neurosciences and Sensory Organs, Aldo Moro University of Bari, Bari, Italy 74Laboratory of Statistical Genetics, The Rockfeller University, 1230 York Avenue, New York, NY, 10065, USA

Acknowledgements We thank the MRC Centre for Neuropsychiatric Genetics and Genomics for supporting this project and the MRC for supporting author Emily Baker. This project was also supported by Dementia Project UK (DPUK). Data used in the preparation of this article were obtained from the Genetic and Environmental Risk for Alzheimer’s disease (GERAD1) Consortium (Harold et al. [2009]). We also thank the Dementia Research Institute (DRI) for supporting this project.

We thank the International Genomics of Alzheimer’s Project (IGAP) for providing summary results data for these analyses. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. bioRxiv preprint doi: https://doi.org/10.1101/374876; this version posted July 23, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

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