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1. Genetic, transcriptomic, histological, and biochemical analysis of progressive supranuclear palsy implicates glial activation and novel risk genes

Author

Kurt Farrell, Jack Humphrey, Timothy Chang, Yi Zhao, Yuk Yee Leung, Pavel P. Kuksa, Vishakha Patil, Wan-Ping Lee, Amanda B. Kuzma, Otto Valladares, Laura B. Cantwell, Hui Wang, Ashvin Ravi, Claudia De Sanctis, Natalia Han, Thomas D. Christie, Robina Afzal, Shrishtee Kandoi, Kristen Whitney, Margaret M. Krassner, Hadley Ressler, SoongHo Kim, Diana Dangoor, Megan A. Iida, Alicia Casella, Ruth H. Walker, Melissa J. Nirenberg, Alan E. Renton, Bergan Babrowicz, Giovanni Coppola, Towfique Raj, Günter U. Höglinger, Ulrich Müller, Lawrence I. Golbe, Huw R. Morris, John Hardy, Tamas Revesz, Tom T. Warner, Zane Jaunmuktane, Kin Y. Mok, Rosa Rademakers, Dennis W. Dickson, Owen A. Ross, Li-San Wang, Alison Goate, Gerard Schellenberg, Daniel H. Geschwind, PSP Genetics Study Group, John F. Crary, and Adam Naj

Subjects
Science
Abstract

Abstract Progressive supranuclear palsy (PSP), a rare Parkinsonian disorder, is characterized by problems with movement, balance, and cognition. PSP differs from Alzheimer’s disease (AD) and other diseases, displaying abnormal microtubule-associated protein tau by both neuronal and glial cell pathologies. Genetic contributors may mediate these differences; however, the genetics of PSP remain underexplored. Here we conduct the largest genome-wide association study (GWAS) of PSP which includes 2779 cases (2595 neuropathologically-confirmed) and 5584 controls and identify six independent PSP susceptibility loci with genome-wide significant (P

Published
2024
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2. Author Correction: Genetic, transcriptomic, histological, and biochemical analysis of progressive supranuclear palsy implicates glial activation and novel risk genes

Author

Kurt Farrell, Jack Humphrey, Timothy Chang, Yi Zhao, Yuk Yee Leung, Pavel P. Kuksa, Vishakha Patil, Wan-Ping Lee, Amanda B. Kuzma, Otto Valladares, Laura B. Cantwell, Hui Wang, Ashvin Ravi, Claudia De Sanctis, Natalia Han, Thomas D. Christie, Robina Afzal, Shrishtee Kandoi, Kristen Whitney, Margaret M. Krassner, Hadley Ressler, SoongHo Kim, Diana Dangoor, Megan A. Iida, Alicia Casella, Ruth H. Walker, Melissa J. Nirenberg, Alan E. Renton, Bergan Babrowicz, Giovanni Coppola, Towfique Raj, Günter U. Höglinger, Ulrich Müller, Lawrence I. Golbe, Huw R. Morris, John Hardy, Tamas Revesz, Tom T. Warner, Zane Jaunmuktane, Kin Y. Mok, Rosa Rademakers, Dennis W. Dickson, Owen A. Ross, Li-San Wang, Alison Goate, Gerard Schellenberg, Daniel H. Geschwind, PSP Genetics Study Group, John F. Crary, and Adam Naj

Subjects
Science
Published
2024
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3. Human whole-exome genotype data for Alzheimer’s disease

Author

Yuk Yee Leung, Adam C. Naj, Yi-Fan Chou, Otto Valladares, Michael Schmidt, Kara Hamilton-Nelson, Nicholas Wheeler, Honghuang Lin, Prabhakaran Gangadharan, Liming Qu, Kaylyn Clark, Amanda B. Kuzma, Wan-Ping Lee, Laura Cantwell, Heather Nicaretta, Alzheimer’s Disease Sequencing Project, Jonathan Haines, Lindsay Farrer, Sudha Seshadri, Zoran Brkanac, Carlos Cruchaga, Margaret Pericak-Vance, Richard P. Mayeux, William S. Bush, Anita Destefano, Eden Martin, Gerard D. Schellenberg, and Li-San Wang

Subjects
Science
Abstract

Abstract The heterogeneity of the whole-exome sequencing (WES) data generation methods present a challenge to a joint analysis. Here we present a bioinformatics strategy for joint-calling 20,504 WES samples collected across nine studies and sequenced using ten capture kits in fourteen sequencing centers in the Alzheimer’s Disease Sequencing Project. The joint-genotype called variant-called format (VCF) file contains only positions within the union of capture kits. The VCF was then processed specifically to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41% of the variants are intronic and 1.8% of the variants are with CADD > 30, indicating they are of high predicted pathogenicity. Here we show our new strategy can generate high-quality data from processing these diversely generated WES samples. The improved ability to combine data sequenced in different batches benefits the whole genomics research community.

Published
2024
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4. Copy Number Variation Identification on 3,800 Alzheimer’s Disease Whole Genome Sequencing Data from the Alzheimer’s Disease Sequencing Project

Author

Wan-Ping Lee, Albert A. Tucci, Mitchell Conery, Yuk Yee Leung, Amanda B. Kuzma, Otto Valladares, Yi-Fan Chou, Wenbin Lu, Li-San Wang, Gerard D. Schellenberg, and Jung-Ying Tzeng

Subjects
copy number variation—CNV, Alzheiemer’s disease, whole-genome sequence (WGS), CNV association test, NGS—next generation sequencing, Genetics, QH426-470
Abstract

Alzheimer’s Disease (AD) is a progressive neurologic disease and the most common form of dementia. While the causes of AD are not completely understood, genetics plays a key role in the etiology of AD, and thus finding genetic factors holds the potential to uncover novel AD mechanisms. For this study, we focus on copy number variation (CNV) detection and burden analysis. Leveraging whole-genome sequence (WGS) data released by Alzheimer’s Disease Sequencing Project (ADSP), we developed a scalable bioinformatics pipeline to identify CNVs. This pipeline was applied to 1,737 AD cases and 2,063 cognitively normal controls. As a result, we observed 237,306 and 42,767 deletions and duplications, respectively, with an average of 2,255 deletions and 1,820 duplications per subject. The burden tests show that Non-Hispanic-White cases on average have 16 more duplications than controls do (p-value 2e-6), and Hispanic cases have larger deletions than controls do (p-value 6.8e-5).

Published
2021
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5. Alzheimer’s Disease Variant Portal: A Catalog of Genetic Findings for Alzheimer’s Disease

Author

Pavel P, Kuksa, Chia-Lun, Liu, Wei, Fu, Liming, Qu, Yi, Zhao, Zivadin, Katanic, Kaylyn, Clark, Amanda B, Kuzma, Pei-Chuan, Ho, Kai-Teh, Tzeng, Otto, Valladares, Shin-Yi, Chou, Adam C, Naj, Gerard D, Schellenberg, Li-San, Wang, and Yuk Yee, Leung

Subjects
Psychiatry and Mental health, Clinical Psychology, Alzheimer Disease, Endophenotypes, General Neuroscience, Humans, Genetic Predisposition to Disease, General Medicine, Geriatrics and Gerontology, Polymorphism, Single Nucleotide, Genome-Wide Association Study
Abstract

Background: Recent Alzheimer’s disease (AD) genetics findings from genome-wide association studies (GWAS) span progressively larger and more diverse populations and outcomes. Currently, there is no up-to-date resource providing harmonized and searchable information on all AD genetic associations found by GWAS, nor linking the reported genetic variants and genes with functional and genomic annotations. Objective: Create an integrated/harmonized, and literature-derived collection of population-specific AD genetic associations. Methods: We developed the Alzheimer’s Disease Variant Portal (ADVP), an extensive collection of associations curated from >200 GWAS publications from Alzheimer’s Disease Genetics Consortium and other consortia. Genetic associations were systematically extracted, harmonized, and annotated from both the genome-wide significant and suggestive loci reported in these publications. To ensure consistent representation of AD genetic findings, all the extracted genetic association information was harmonized across specifically designed publication, variant, and association categories. Results: ADVP V1.0 (February 2021) catalogs 6,990 associations related to disease-risk, expression quantitative traits, endophenotypes, or neuropathology. This extensive harmonization effort led to a catalog containing >900 loci, >1,800 variants, >80 cohorts, and 8 populations. Besides, ADVP provides investigators with a seamless integration of genomic and publicly available functional annotations across multiple databases per harmonized variant and gene records, thus facilitating further understanding and analyses of these genetics findings. Conclusion: ADVP is a valuable resource for investigators to quickly and systematically explore high-confidence AD genetic findings and provides insights into population-specific AD genetic architecture. ADVP is continually maintained and enhanced by NIAGADS and is freely accessible at https://advp.niagads.org.

Published
2022
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6. NIAGADS Alzheimer’s Genomics Database: version GRCh38

Author

Emily Greenfest‐Allen, Pavel P. Kuksa, Amanda B Kuzma, Otto Valladares, Wan‐Ping Lee, Nicholas R. Wheeler, William S. Bush, Yuk Yee Leung, Christian J Stoeckert, and Li‐San Wang

Subjects
Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Geriatrics and Gerontology
Published
2022
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7. The Alzheimer’s Disease Sequencing Project Follow Up Study (ADSP‐FUS): increasing ethnic diversity in Alzheimer’s disease (AD) genetics research

Author

Pedro Ramon Mena, Brian W. Kunkle, Kelley M. Faber, Larry D. Adams, Jovita D. Inciute, Patrice L. Whitehead, Tatiana M. Foroud, Dolly Reyes‐Dumeyer, Amanda B Kuzma, Yuk Yee Leung, Adam C. Naj, Eden R. Martin, Clifton L. Dalgard, Gerard D. Schellenberg, Li‐San Wang, Richard Mayeux, Badri N. Vardarajan, Jeffery M. Vance, Michael L. Cuccaro, and Margaret A. Pericak‐Vance

Subjects
Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Geriatrics and Gerontology
Published
2022
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8. NIA Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS): 2022 Update

Author

Heather Issen, Amanda B Kuzma, Otto Valladares, Emily Greenfest‐Allen, Conor Klamann, Prabhakaran Gangadharan, Zivadin Katanic, Andrew Wilk, Yi Zhao, Liming Qu, Michelle K Moon, Alexis Lerro Rose, Joseph Manuel, Peter Keskinen, Carlos Thomas, Shin‐Yi Chou, Wan‐Ping Lee, Yuk Yee Leung, Adam C. Naj, Christian J Stoeckert, Gerard D. Schellenberg, and Li‐San Wang

Subjects
Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Geriatrics and Gerontology
Published
2022
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9. A comparative study of structural variant calling strategies using the Alzheimer’s Disease Sequencing Project’s whole genome family data

Author

John S. Malamon, John J. Farrell, Li Charlie Xia, Beth A. Dombroski, Wan-Ping Lee, Rueben G. Das, Badri N. Vardarajan, Jessica Way, Amanda B. Kuzma, Otto Valladares, Yuk Yee Leung, Allison J. Scanlon, Irving Antonio Barrera Lopez, Jack Brehony, Kim C. Worley, Nancy R. Zhang, Li-San Wang, Lindsay A. Farrer, and Gerard D. Schellenberg

Abstract

BackgroundReliable detection and accurate genotyping of structural variants (SVs) and insertion/deletions (indels) from whole-genome sequence (WGS) data is a significant challenge. We present a protocol for variant calling, quality control, call merging, sensitivity analysis, in silico genotyping, and laboratory validation protocols for generating a high-quality deletion call set from whole genome sequences as part of the Alzheimer’s Disease Sequencing Project (ADSP). This dataset contains 578 individuals from 111 families.MethodsWe applied two complementary pipelines (Scalpel and Parliament) for SV/indel calling, break-point refinement, genotyping, and local reassembly to produce a high-quality annotated call set. Sensitivity was measured in sample replicates (N=9) for all callers using in silico variant spike-in for a wide range of event sizes. We focused on deletions because these events were more reliably called. To evaluate caller specificity, we developed a novel metric called the D-score that leverages deletion sharing frequencies within and outside of families to rank recurring deletions. Assessment of overall quality across size bins was measured with the kinship coefficient. Individual callers were evaluated for computational cost, performance, sensitivity, and specificity. Quality of calls were evaluated by Sanger sequencing of predicted loss-of-function (LOF) variants, variants near AD candidate genes, and randomly selected genome-wide deletions ranging from 2 to 17,000 bp.ResultsWe generated a high-quality deletion call set across a wide range of event sizes consisting of 152,301 deletions with an average of 263 per genome. A total of 114 of 146 predicted deletions (78.1%) were validated by Sanger sequencing. Scalpel was more accurate in calling deletions ≤100 bp, whereas for Parliament, sensitivity was improved for deletions > 900 bp. We validated 83.0% (88/106) and 72.5% (37/51) of calls made by Scalpel and Parliament, respectively. Eleven deletions called by both Parliament and Scalpel in the 101-900 bin were tested and all were confirmed by Sanger sequencing.ConclusionsWe developed a flexible protocol to assess the quality of deletion detection across a wide range of sizes. We also generated a truth set of Sanger sequencing validated deletions with precise breakpoints covering a wide spectrum of sizes between 1 and 17,000 bp.

Published
2022
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10. Inferring the Molecular Mechanisms of Noncoding Alzheimer’s Disease-Associated Genetic Variants

Author

Jessica Way, Yuk Yee Leung, Amanda B. Kuzma, Beth A. Dombroski, Yi Zhao, Elisabeth E. Mlynarski, Yi-Fan Chou, Alexandre Amlie-Wolf, Gerard D. Schellenberg, Li-San Wang, Ming Jiang, Nicholas Vrettos, Christopher D. Brown, and Mitchell Tang

Subjects
0301 basic medicine, Linkage disequilibrium, Genomics, Locus (genetics), Genome-wide association study, Computational biology, Biology, Article, Linkage Disequilibrium, ABCA7, 03 medical and health sciences, 0302 clinical medicine, Alzheimer Disease, Genetic variation, Humans, Genetic Predisposition to Disease, Enhancer, Gene, 030304 developmental biology, Genetic association, 0303 health sciences, General Neuroscience, Genetic Variation, General Medicine, 3. Good health, Psychiatry and Mental health, Clinical Psychology, 030104 developmental biology, Expression quantitative trait loci, biology.protein, Geriatrics and Gerontology, Functional genomics, Algorithms, Function (biology), 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

More than 20 genetic variants associated with late-onset Alzheimer’s disease (LOAD) have been identified by genome-wide association studies (GWAS). However, these variants are tag markers for nearby genetic variants in linkage disequilibrium (LD) and may not be themselves functional. Moreover, most of the significant variants identified by the International Genomics of Alzheimer’s Project (IGAP) meta-analysis are in non-protein-coding regions, implicating gene regulatory mechanisms as underlying the association signal. There are several previously identified coding variant associations with AD, notably the strong APOE signal, but all the novel signals identified in the IGAP GWAS were noncoding. We set out to characterize the causal variants, regulatory mechanisms, tissue contexts, and target genes underlying noncoding LOAD-associated genetic signals. To do so, we applied our INFERNO method to the IGAP GWAS data, annotating all LD-expanded potentially causal variants at each locus with tissue-specific regulatory activity. Bayesian co-localization analysis of GWAS summary statistics and eQTL data was performed to identify tissue-specific target genes. INFERNO identified enhancer dysregulation in all 19 tag regions analyzed, significant enrichments of enhancer overlaps in the immune-related blood category, and co-localized eQTL signals overlapping enhancers from the matching tissue class in ten regions (ABCA7, BIN1, CASS4, CD2AP, CD33, CELF1, CLU, EPHA1, FERMT2, ZCWPW1). In several cases, we identified dysregulation of long noncoding RNA (lncRNA) transcripts and applied the lncRNA target identification algorithm from INFERNO to characterize their downstream biological effects. We also validated the allele-specific effects of several variants on enhancer function using luciferase expression assays. Integrating functional genomics with GWAS signals yielded insights into the regulatory mechanisms, tissue contexts, genes, and biological processes affected by noncoding genetic variation associated with LOAD risk.

Published
2019
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11. Genome-Wide Meta-Analysis of Late-Onset Alzheimer’s Disease Using Rare Variant Imputation in 65,602 Subjects Identifies Novel Rare Variant Locus NCK2: The International Genomics of Alzheimer’s Project (IGAP)

Author

Yuk Yee Leung, Lindsay A. Farrer, Yi Zhao, Amanda B. Kuzma, Jean-Charles Lambert, Alessandra Chesi, Xia R, Haines Jl, Haut J, Anita L. DeStefano, Chouraki, Julie Williams, William S. Bush, Leonenko G, Achilleas N. Pitsillides, John J. Farrell, Richard Mayeux, Fulton-Howard B, Xueqiu Jian, van Duijn C, Edward B. Lee, Sudha Seshadri, Sandra Barral, Li M, Jennifer E. Below, Rebecca Sims, Kara L. Hamilton-Nelson, J. C. Bis, Céline Bellenguez, Struan F.A. Grant, Otto Valladares, B. Grenier-Boley, Schellenberg Gd, Peter Holmans, Margaret A. Pericak-Vance, Comic H, Maria Carolina Dalmasso, Badri N. Vardarajan, Penelope Benchek, Phillips-Cremins Je, Philippe Amouyel, Brian W. Kunkle, Adam C. Naj, Zhang Y, Alfredo Ramirez, Pavel P. Kuksa, Chen H, Jin Sha, Li-San Wang, Lee C, van der Lee Sj, and Josée Dupuis

Subjects
Genetics, 0303 health sciences, TREM2, Haplotype, Genome-wide association study, Locus (genetics), Biology, Minor allele frequency, 03 medical and health sciences, 0302 clinical medicine, Genotype, 030217 neurology & neurosurgery, Imputation (genetics), 030304 developmental biology, Genetic association
Abstract

Risk for late-onset Alzheimer’s disease (LOAD) is driven by multiple loci primarily identified by genome-wide association studies, many of which are common variants with minor allele frequencies (MAF)> 0.01. To identify additional common and rare LOAD risk variants, we performed a GWAS on 25,170 LOAD subjects and 41,052 cognitively normal controls in 44 datasets from the International Genomics of Alzheimer’s Project (IGAP). Existing genotype data was imputed using the dense, high-resolution Haplotype Reference Consortium (HRC) r1.1 reference panel. Stage 1 associations of P−5 were meta-analyzed with the European Alzheimer’s Disease Biobank (EADB) (n=20,301 cases; 21,839 controls) (stage 2 combined IGAP and EADB). An expanded meta-analysis was performed using a GWAS of parental AD/dementia history in the UK Biobank (UKBB) (n=35,214 cases; 180,791 controls) (stage 3 combined IGAP, EADB, and UKBB). Common variant (MAF≥0.01) associations were identified for 29 loci in stage 2, including novel genome-wide significant associations at TSPAN14 (P=2.33×10−12), SHARPIN (P=1.56×10−9), and ATF5/SIGLEC11 (P=1.03×10−8), and newly significant associations without using AD proxy cases in MTSS1L/IL34 (P=1.80×10−8), APH1B (P=2.10×10−13), and CLNK (P=2.24×10−10). Rare variant (MAFAPOE and TREM2, and a novel association of a rare variant (rs143080277; MAF=0.0054; P=2.69×10−9) in NCK2, further strengthened with the inclusion of UKBB data in stage 3 (P=7.17×10−13). Single-nucleus sequence data shows that NCK2 is highly expressed in amyloid-responsive microglial cells, suggesting a role in LOAD pathology.

Published
2021
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12. Genome‐wide meta‐analysis of late‐onset Alzheimer’s disease using rare variant imputation in 65,602 subjects identifies risk loci with roles in memory, neurodevelopment, and cardiometabolic traits: The international genomics of Alzheimer’s project (IGAP)

Author

Brian W. Kunkle, Amanda B. Kuzma, Adam C. Naj, Brian Fulton-Howard, Philippe Amouyel, Julie Williams, Ganna Leonenko, Peter Holmans, Jin Sha, Jonathan L. Haines, Li-San Wang, Benjamin Grenier-Boley, Alfredo Ramirez, Xueqiu Jian, J. C. Bis, Vincent Chouraki, Rebecca Sims, Josée Dupuis, Yi Zhao, Cornelia M. van Duijn, Gerard D. Schellenberg, Achilleas N. Pitsillides, Anita L. DeStefano, Sudha Seshadri, Hata Karamujić-Čomić, Jean-Charles Lambert, Maria Carolina Dalmasso, Lindsay A. Farrer, Margaret A. Pericak-Vance, Sven J. van der Lee, and Rui Xia

Subjects
Genetics, Epidemiology, Health Policy, Genomics, Late onset, Disease, Biology, Omics, Genome, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Meta-analysis, Neurology (clinical), Geriatrics and Gerontology, Imputation (genetics)
Published
2020
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13. NIA genetics of Alzheimer’s disease data storage site (NIAGADS): Update 2020

Author

Li-San Wang, Yuk Yee Leung, Briana Vogel, Amanda B. Kuzma, Liming Qu, Otto Valladares, Conor Klamann, Yi Zhao, Han-Jen Lin, Adam C. Naj, Zivadin Katanic, Heather Issen, Gerard D. Schellenberg, Michelle K. Moon, Prabhakaran Gangadharan, Christian J. Stoeckert, and Emily Greenfest-Allen

Subjects
Genetics, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Disease, Geriatrics and Gerontology, Biology
Published
2020
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14. Alzheimer’s disease variant portal (ADVP): Harmonized genetics data and evidence collection for Alzheimer’s disease

Author

Pavel P. Kuksa, Wei Fu, Li-San Wang, Adam C. Naj, Kai-Teh Tzeng, Gerard D. Schellenberg, Chia-Lun Liu, Otto Valladares, Yuk Yee Leung, Amanda B. Kuzma, Liming Qu, Shin-Yi Chou, Zivadin Katanic, and Yi Zhao

Subjects
Genetics, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, business.industry, Health Policy, Medicine, Neurology (clinical), Disease, Evidence collection, Geriatrics and Gerontology, business
Published
2020
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15. The Alzheimer’s disease sequencing project–follow up study (ADSP‐FUS): Increasing ethnic diversity in Alzheimer’s genetics research with addition of potential new cohorts

Author

Gerard D. Schellenberg, Pedro Ramon Mena, Badri N. Vardarajan, Tatiana Foroud, Kelley Faber, Clifton L. Dalgard, Richard Mayeux, Li-San Wang, Amanda B. Kuzma, Jeffery M. Vance, Katrina Celis, Margaret A. Pericak-Vance, Dolly Reyes-Dumeyer, Brian W. Kunkle, Adam C. Naj, Larry D. Adams, Eden R. Martin, and Michael L. Cuccaro

Subjects
Genetics, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Cultural diversity, Follow up studies, Neurology (clinical), Disease, Geriatrics and Gerontology, Biology
Published
2020
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16. Alzheimer’s Disease variant portal (ADVP): a catalog of genetic findings for Alzheimer’s Disease

Author

Kai-Teh Tzeng, Chia-Lun Liu, Gerard D. Schellenberg, Otto Valladares, Adam C. Naj, Pei-Chuan Ho, Li-San Wang, Yi Zhao, Zivadin Katanic, Yuk Yee Leung, Amanda B. Kuzma, Pavel P. Kuksa, Wei Fu, Shin-Yi Chou, and Liming Qu

Subjects
education.field_of_study, Endophenotype, Population, Genome-wide association study, Neuropathology, Computational biology, Disease, Quantitative trait locus, Biology, education, Genetic architecture, Genetic association
Abstract

Alzheimer’s Disease (AD) genetics has made substantial progress through genome-wide association studies (GWASs). An up-to-date resource providing harmonized, searchable information on AD genetic variants with linking to genes and supporting functional evidence is needed.We developed the Alzheimer’s Disease Variant Portal (ADVP), an extensive collection of associations curated from >200 GWAS publications from Alzheimer’s Disease Genetics Consortium (ADGC) and other researchers. Publications are reviewed systematically to extract top associations for harmonization and genomic annotation.ADVP V1.0 catalogs 6,990 associations with disease-risk, expression quantitative traits, endophenotypes and neuropathology across >900 loci, >1,800 variants, >80 cohorts, and 8 populations. ADVP integrates with NIAGADS Alzheimer’s GenomicsDB where investigators can cross-reference other functional evidence.ADVP is a valuable resource for investigators to quickly and systematically explore high-confidence AD genetic findings and provides insights into population- and tissue-specific AD genetic architecture. ADVP is continually maintained and enhanced by NIAGADS and is freely accessible (https://advp.niagads.org).

Published
2020
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17. NIAGADS Alzheimer’s GenomicsDB: A resource for exploring Alzheimer’s Disease genetic and genomic knowledge

Author

Emily Greenfest-Allen, Otto Valladares, Pavel P. Kuksa, Prabhakaran Gangadharan, Wan-Ping Lee, Jeffrey Cifello, Zivadin Katanic, Amanda B. Kuzma, Nicholas Wheeler, William S. Bush, Yuk Yee Leung, Gerard Schellenberg, Christian J. Stoeckert, and Li-San Wang

Subjects
Resource (project management), Computer science, Genomics, Genome-wide association study, Gene Annotation, Computational biology, Functional genomics, Gene, DNA sequencing
Abstract

INTRODUCTION: The NIAGADS Alzheimer9s Genomics Database is an interactive knowledgebase for AD genetics that provides access to GWAS summary statistics datasets deposited at NIAGADS, a national genetics data repository for AD and related dementia (ADRD). METHODS: The website makes available >70 genome-wide summary statistics datasets from GWAS and genome sequencing analysis for AD/ADRD. Variants identified from these datasets are mapped to up-to-date variant and gene annotations from a variety of resources and linked to functional genomics data. The database is powered by a big-data optimized relational database and uses ontologies to consistently annotate study designs and phenotypes, facilitating data harmonization and efficient real-time data analysis and variant or gene report generation. RESULTS: Detailed variant reports provide tabular and interactive graphical summaries of known ADRD associations, as well as highlight variants flagged by the Alzheimer9s Disease Sequencing Project (ADSP). Gene reports provide summaries of co-located ADRD risk-associated variants and have been expanded to include meta-analysis results from aggregate association tests performed by the ADSP allowing us to flag genes with genetic-evidence for AD. DISCUSSION: The GenomicsDB makes available >100 million variant annotations, including ~30 million (5 million novel) variants identified as AD-relevant by ADSP, for browsing and real-time mining via the website or programmatically through a REST API. With a newly redesigned, efficient, search interface and comprehensive record pages linking summary statistics to variant and gene annotations, this resource makes these data both accessible and interpretable, establishing itself as valuable tool for AD research.

Published
2020
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18. Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into the complex genetic architecture

Author

Pentti J. Tienari, James B. Leverenz, Nahid Tayebi, Gabriele Mora, Bradley F. Boeve, Laura Palmer, Steve M. Gentleman, Ellen Sidransky, Pau Pastor, Liana S. Rosenthal, G. Xiromerisiou, Sara Saez-Atienzar, Francesco Landi, Scott M. Kaiser, Qinwen Mao, Claire Troakes, Peter St George-Hyslop, Andrea Calvo, Suzanne Lesage, Mario Masellis, Randy Woltjer, Marilyn S. Albert, Thomas T. Warner, Lorraine N. Clark, Gregory Klein, Charles Duyckaerts, Seth Love, Ed Monuki, Lawrence S. Honig, Kelley Faber, Dennis W. Dickson, Lucy Norcliffe-Kaufmann, Cornelis Blauwendraat, Ronald C. Kim, Kevin Morgan, Clifton L. Dalgard, Joshua T. Geiger, Ali Torkamani, Jinhui Ding, Juan Fortea, Eliezer Masliah, Ekaterina Rogaeva, Matthew H. Perkins, Clemens R. Scherzer, John Q. Trojanowski, Zbigniew K. Wszolek, Glenda M. Halliday, Jordi Clarimón, Sonja W. Scholz, Olaf Ansorge, Makayla K. Portley, Toshiko Tanaka, Mary B. Makarious, Safa Al-Sarraj, Giancarlo Logroscino, John D. Eicher, Neill R. Graff-Radford, Carmen Lage, Ziv Gan-Or, Francesca Brett, Alison Goate, Raffaele Ferrari, John C. Morris, J. Raphael Gibbs, Lynn M. Bekris, Jose-Alberto Palma, Angela K. Hodges, Regina H. Reynolds, Alexis Brice, Monica Diez-Fairen, Coralie Viollet, Patrick May, Minna Oinas, Erika Salvi, Vivianna M. Van Deerlin, Estrella Morenas-Rodríguez, Anni Moore, Zane Jaunmuktane, Eileen H. Bigio, Daniele Cusi, Douglas Galasko, Ruth Chia, Kathy L. Newell, Isabel Santana, Claudia Schulte, David Goldstein, Thomas Gasser, Owen A. Ross, Walter A. Kukull, Tatiana Foroud, Chad A. Caraway, David A. Bennett, Samreen Ahmed, Lilah M. Besser, Antonio Canosa, Daniel Alcolea, Yevgeniya Abramzon, Elisabet Londos, Laura Parkkinen, Sandra E. Black, Eric Topol, Marya S. Sabir, Olga Pletnikova, Grisel Lopez, Tanis J. Ferman, Johannes Attems, Matthew J. Barrett, Margaret E. Flanagan, Horacio Kaufmann, Stuart Pickering Brown, Jon Infante, Ryan C. Bohannan, Alberto Lleó, Eloy Rodríguez-Rodríguez, Huw R. Morris, Gianluca Floris, Ted M. Dawson, Maura Brunetti, Alan E. Renton, Andrew B. Singleton, Karen Marder, Alan J. Thomas, Pascual Sanchez-Juan, Adriano Chiò, Nigel J. Cairns, David J. Stone, Tammaryn Lashley, Mike A. Nalls, Bernardino Ghetti, Sara Bandres-Ciga, Zalak Shah, Ian G. McKeith, Susan M. Resnick, Julia Keith, Liisa Myllykangas, Diego Albani, Christopher M. Morris, Vikram Shakkottai, M. Ryten, Ronald L. Walton, Isabel González-Aramburu, Luigi Ferrucci, Bryan J. Traynor, Amanda B. Kuzma, Afina W. Lemstra, Thomas G. Beach, Juan C. Troncoso, Emil K. Gustavsson, Maurizio Grassano, John Hardy, Geidy E. Serrano, Rejko Krüger, Dag Aarsland, Bension S. Tilley, and Dena G. Hernandez

Subjects
0303 health sciences, Lewy body, Disease, Computational biology, Biology, medicine.disease, DNA sequencing, Genetic architecture, 03 medical and health sciences, 0302 clinical medicine, medicine, Dementia, Genetic risk, Gene, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer’s and Parkinson’s disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.

Published
2020
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19. Whole exome sequencing study identifies novel rare and common Alzheimer’s-Associated variants involved in immune response and transcriptional regulation

Author

Joshua C. Bis, Li-San Wang, Waleed Nasser, Giuseppe Tosto, Jean-Charles Lambert, Gary W. Beecham, Lucinda Fulton, Eric Boerwinkle, Reinhold Schmidt, Kara L. Hamilton-Nelson, Josée Dupuis, Cornelia M. van Duijn, Yuning Chen, Stéphanie Debette, Devanshi Patel, Philippe Amouyel, Gaël Nicolas, Farid Rajabli, Mark J. Daly, Richard Redon, Hilkka Soininen, Anita L. DeStefano, Aki S. Havulinna, Weixin Wang, Margaret A. Pericak-Vance, Chloé Sarnowski, Gerard D. Schellenberg, William S. Bush, Eden R. Martin, John J. Farrell, Richard A. Gibbs, Richard Mayeux, Emmanuelle Génin, Yi Zhao, Kwangsik Nho, Céline Bellenguez, Kari Mattila, Jean-François Deleuze, William J Salerno, Alzheimer’s Disease Sequencing, Brian W. Kunkle, Dominique Campion, Mikko Hiltunen, Richard K. Wilson, Sudha Seshadri, Paul K. Crane, Otto Valladares, Jennifer E. Below, Adam C. Naj, Timothy A. Thornton, Stacey Gabriel, Jan Konrad, Markus Perola, Mark Lathrop, Namrata Gupta, Badri N. Vardarajan, Bruce M. Psaty, Seppo Helisalmi, Jonathan L. Haines, Yiyi Ma, Honghuang Lin, Laura B. Cantwell, Carlos Cruchaga, Alan E. Renton, Terho Lehtimäki, Anne M. Remes, Michael A. Schmidt, Benjamin M. Neale, M. Arfan Ikram, Lindsay A. Farrer, Myriam Fornage, Daniel P. Howrigan, Ellen M. Wijsman, Mitja I. Kurki, Helena Schmidt, Aarno Palotie, Daniel Lancour, Camille Charbonnier, Daniela Witten, Liming Qu, Najaf Amin, Eric S. Lander, Alison Goate, Donna M. Muzny, Kathryn L. Lunetta, Jaakko Kaprio, Edoardo Marcora, Amanda B. Kuzma, Sven J. van der Lee, Shahzad Ahmad, Kim C. Worley, Christophe Tzourio, Benjamin Grenier-Boley, Jean-François Dartigues, L. Adrienne Cupples, Veikko Salomaa, Jaeyoon Chung, Christiane Reitz, Xueqiu Jian, Xiaoling Zhang, Olivier Quenez, Medicum, Institute for Molecular Medicine Finland, Complex Disease Genetics, University of Helsinki, Centre of Excellence in Complex Disease Genetics, Research Programs Unit, Aarno Palotie / Principal Investigator, Genomics of Neurological and Neuropsychiatric Disorders, HUS Helsinki and Uusimaa Hospital District, Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Génomique et Médecine Personnalisée du Cancer et des Maladies Neuropsychiatriques (GPMCND), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Rouen, Normandie Université (NU), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Bordeaux [Bordeaux], Centre National de Recherche en Génomique Humaine (CNRGH), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Génétique, génomique fonctionnelle et biotechnologies (UMR 1078) (GGB), EFS-Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO), Unité de recherche de l'institut du thorax (ITX-lab), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO)-EFS-Institut National de la Santé et de la Recherche Médicale (INSERM), unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Epidemiology

Subjects
Male, 0301 basic medicine, DYSBINDIN GENE DTNBP1, Transcription, Genetic, [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, SORL1, PROTEIN, Diseases, Genome-wide association study, SUSCEPTIBILITY, [SDV.IMM.II]Life Sciences [q-bio]/Immunology/Innate immunity, DISEASE, ABCA7, 0302 clinical medicine, Exome sequencing, Aged, 80 and over, Genetics, RISK, 3. Good health, Psychiatry and Mental health, [SDV.IMM.IA]Life Sciences [q-bio]/Immunology/Adaptive immunology, Female, RNA, Long Noncoding, Alzheimer's disease, Immunoglobulin gene, EXPRESSION, Kruppel-Like Transcription Factors, Biology, Article, CODING MUTATIONS, 03 medical and health sciences, Cellular and Molecular Neuroscience, Apolipoproteins E, Alzheimer Disease, Exome Sequencing, medicine, Humans, GENOME-WIDE ASSOCIATION, Molecular Biology, Gene, Genotyping, Aged, Amyloid beta-Peptides, Polymorphism, Genetic, [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], Haplotype, Immunity, 3112 Neurosciences, Correction, medicine.disease, 030104 developmental biology, Gene Expression Regulation, Haplotypes, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Immunoglobulin G, 3111 Biomedicine, 030217 neurology & neurosurgery
Abstract

The Alzheimer’s Disease Sequencing Project (ADSP) undertook whole exome sequencing in 5,740 late-onset Alzheimer disease (AD) cases and 5,096 cognitively normal controls primarily of European ancestry (EA), among whom 218 cases and 177 controls were Caribbean Hispanic (CH). An age-, sex- and APOE based risk score and family history were used to select cases most likely to harbor novel AD risk variants and controls least likely to develop AD by age 85 years. We tested ~1.5 million single nucleotide variants (SNVs) and 50,000 insertion-deletion polymorphisms (indels) for association to AD, using multiple models considering individual variants as well as gene-based tests aggregating rare, predicted functional, and loss of function variants. Sixteen single variants and 19 genes that met criteria for significant or suggestive associations after multiple-testing correction were evaluated for replication in four independent samples; three with whole exome sequencing (2,778 cases, 7,262 controls) and one with genome-wide genotyping imputed to the Haplotype Reference Consortium panel (9,343 cases, 11,527 controls). The top findings in the discovery sample were also followed-up in the ADSP whole-genome sequenced family-based dataset (197 members of 42 EA families and 501 members of 157 CH families). We identified novel and predicted functional genetic variants in genes previously associated with AD. We also detected associations in three novel genes: IGHG3 (p = 9.8 × 10−7), an immunoglobulin gene whose antibodies interact with β-amyloid, a long non-coding RNA AC099552.4 (p = 1.2 × 10−7), and a zinc-finger protein ZNF655 (gene-based p = 5.0 × 10−6). The latter two suggest an important role for transcriptional regulation in AD pathogenesis.

Published
2018
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20. Functional annotation of genomic variants in studies of late-onset Alzheimer’s disease

Author

Alan E. Renton, Yuk Yee Leung, Amanda B. Kuzma, Edoardo Marcora, Daniel C. Koboldt, Li-San Wang, Jonathan L. Haines, Mariusz Butkiewicz, Elizabeth E. Blue, William S. Bush, and Xueqiu Jian

Subjects
0301 basic medicine, Statistics and Probability, Sequence analysis, Computer science, Genomics, Disease, Computational biology, Polymorphism, Single Nucleotide, Biochemistry, Genome, 03 medical and health sciences, Annotation, Alzheimer Disease, Databases, Genetic, Humans, Genetic Predisposition to Disease, Potential analysis, Molecular Biology, Gene, Molecular Sequence Annotation, Sequence Analysis, DNA, Genome Analysis, Original Papers, Computer Science Applications, Computational Mathematics, ComputingMethodologies_PATTERNRECOGNITION, 030104 developmental biology, Computational Theory and Mathematics, Functional annotation, Software
Abstract

Motivation Annotation of genomic variants is an increasingly important and complex part of the analysis of sequence-based genomic analyses. Computational predictions of variant function are routinely incorporated into gene-based analyses of rare-variants, though to date most studies use limited information for assessing variant function that is often agnostic of the disease being studied. Results In this work, we outline an annotation process motivated by the Alzheimer’s Disease Sequencing Project, illustrate the impact of including tissue-specific transcript sets and sources of gene regulatory information and assess the potential impact of changing genomic builds on the annotation process. While these factors only impact a small proportion of total variant annotations (∼5%), they influence the potential analysis of a large fraction of genes (∼25%). Availability and implementation Individual variant annotations are available via the NIAGADS GenomicsDB, at https://www.niagads.org/genomics/ tools-and-software/databases/genomics-database. Annotations are also available for bulk download at https://www.niagads.org/datasets. Annotation processing software is available at http://www.icompbio.net/resources/software-and-downloads/. Supplementary information Supplementary data are available at Bioinformatics online.

Published
2018
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21. NIAGADS: The NIA Genetics of Alzheimer's Disease Data Storage Site

Author

Adam C. Naj, Yuk Yee Leung, Amanda B. Kuzma, John Malamon, Liming Qu, Daniel Micah Childress, Gerard D. Schellenberg, Prabhakaran Gangadharan, Li-San Wang, Emily Greenfest-Allen, Rebecca Cweibel, Christian J. Stoeckert, Yi Zhao, and Otto Valladares

Subjects
0301 basic medicine, Genetics, Gerontology, Epidemiology, business.industry, Health Policy, Genetic data, Disease, Data sharing, 03 medical and health sciences, Psychiatry and Mental health, Cellular and Molecular Neuroscience, 030104 developmental biology, 0302 clinical medicine, Developmental Neuroscience, Medicine, Neurology (clinical), Geriatrics and Gerontology, business, 030217 neurology & neurosurgery, Research data
Abstract

Summary Work in the past 10 years has greatly expanded our understanding of Alzheimer's disease (AD) genetics, with more than 20 susceptibility genetic loci discovered in large genome-wide association and sequencing studies. The NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) is funded by National Institute on Aging to serve as a one-stop portal for the community to access research data and findings generated from AD genetics projects. In this article, we describe the mission of NIAGADS, available resources, and data sets including the Alzheimer's Disease Sequencing Project, and how researchers may apply for access to genetic data.

Published
2016
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22. Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel

Author

James B. Brewer, Marilyn S. Albert, Bradley T. Hyman, Takiyah D. Starks, Russell H. Swerdlow, Jeffery M. Vance, Mary Sano, Gerard D. Schellenberg, Jennifer J. Manly, Walter A. Kukull, Jaeyoon Chung, Temitope Ayodele, Tatiana Foroud, Christiane Reitz, Thomas Wisniewski, Lindsay A. Farrer, Eric B. Larson, Laura B. Cantwell, David A. Bennett, Victor W. Henderson, Kara L. Hamilton-Nelson, Neill R. Graff-Radford, Hugh C. Hendrie, Denis A. Evans, Charles DeCarli, Scott A. Small, Joe D. Buxbaum, Paul K. Crane, M. Ilyas Kamboh, Robert Vassar, Suzanne Craft, M. Daniele Fallin, Richard Mayeux, Jonathan L. Haines, Melissa Jean-Francois, Izri Martinez, Thomas O. Obisesan, Li Sao Wang, John Q. Trojanowski, Jeffrey Kaye, Kathryn L. Lunetta, Frank M. LaFerla, Linda J. Van Eldik, Andrew J. Saykin, Bruce L. Miller, Lisa L. Barnes, Roger N. Rosenberg, John C. Morris, Michael A. Schmidt, Ronald C. Petersen, Eric M. Reiman, Kathleen S. Hall, Michael L. Cuccaro, Gyungah Jun, Goldie S. Byrd, Rodney C.P. Go, Oscar L. Lopez, Alison Goate, Margaret A. Pericak-Vance, Hans-Ulrich Klein, Jesse Mez, Brian W. Kunkle, Adam C. Naj, Thomas J. Grabowski, Eden R. Martin, Allan I. Levey, Larry D. Adams, Henry L. Paulson, James B. Leverenz, Stephen M. Strittmatter, Nilufer Ertekin-Taner, Todd E. Golde, Sanjay Asthana, Neil W. Kowall, Mark W. Logue, Amanda B. Kuzma, Helena C. Chui, and Phil De Jager

Subjects
Male, Apolipoprotein E, Genome-wide association study, Locus (genetics), 03 medical and health sciences, 0302 clinical medicine, Alzheimer Disease, Humans, Medicine, Genetic Predisposition to Disease, 030212 general & internal medicine, Aged, Genetic association, Genetics, business.industry, TREM2, Correction, Middle Aged, medicine.disease, Black or African American, Genetic Loci, Meta-analysis, Etiology, Female, Neurology (clinical), Alzheimer's disease, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Importance Compared with non-Hispanic White individuals, African American individuals from the same community are approximately twice as likely to develop Alzheimer disease. Despite this disparity, the largest Alzheimer disease genome-wide association studies to date have been conducted in non-Hispanic White individuals. In the largest association analyses of Alzheimer disease in African American individuals,ABCA7,TREM2, and an intergenic locus at 5q35 were previously implicated. Objective To identify additional risk loci in African American individuals by increasing the sample size and using the African Genome Resource panel. Design, Setting, and Participants This genome-wide association meta-analysis used case-control and family-based data sets from the Alzheimer Disease Genetics Consortium. There were multiple recruitment sites throughout the United States that included individuals with Alzheimer disease and controls of African American ancestry. Analysis began October 2018 and ended September 2019. Main Outcomes and Measures Diagnosis of Alzheimer disease. Results A total of 2784 individuals with Alzheimer disease (1944 female [69.8%]) and 5222 controls (3743 female [71.7%]) were analyzed (mean [SD] age at last evaluation, 74.2 [13.6] years). Associations with 4 novel common loci centered near the intracellular glycoprotein trafficking geneEDEM1(3p26;P = 8.9 × 10−7), near the immune response geneALCAM(3q13;P = 9.3 × 10−7), withinGPC6(13q31;P = 4.1 × 10−7), a gene critical for recruitment of glutamatergic receptors to the neuronal membrane, and withinVRK3(19q13.33;P = 3.5 × 10−7), a gene involved in glutamate neurotoxicity, were identified. In addition, several loci associated with rare variants, including a genome-wide significant intergenic locus nearIGF1Rat 15q26 (P = 1.7 × 10−9) and 6 additional loci with suggestive significance (P ≤ 5 × 10−7) such asAPI5 at 11p12 (P = 8.8 × 10−8) andRBFOX1at 16p13 (P = 5.4 × 10−7) were identified. Gene expression data from brain tissue demonstrate association ofALCAM, ARAP1, GPC6, andRBFOX1with brain β-amyloid load. Of 25 known loci associated with Alzheimer disease in non-Hispanic White individuals, onlyAPOE,ABCA7,TREM2,BIN1,CD2AP,FERMT2, andWWOXwere implicated at a nominal significance level or stronger in African American individuals. Pathway analyses strongly support the notion that immunity, lipid processing, and intracellular trafficking pathways underlying Alzheimer disease in African American individuals overlap with those observed in non-Hispanic White individuals. A new pathway emerging from these analyses is the kidney system, suggesting a novel mechanism for Alzheimer disease that needs further exploration. Conclusions and Relevance While the major pathways involved in Alzheimer disease etiology in African American individuals are similar to those in non-Hispanic White individuals, the disease-associated loci within these pathways differ.

Published
2021
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23. Biobank-wide association scan identifies risk factors for late-onset Alzheimer’s disease and endophenotypes

Author

Paul K. Crane, Shubhabrata Mukherjee, Timothy J. Hohman, Logan Dumitrescu, Brian W. Kunkle, Adam C. Naj, Yuetiva Deming, Burcu F. Darst, Yan D, Yihong Zhao, Bowen Hu, Sterling C. Johnson, Yen-Wen Wang, Hyunseung Kang, Corinne D. Engelman, Amanda B. Kuzma, and Carlos Cruchaga

Subjects
0303 health sciences, Genome-wide association study, Disease, Computational biology, Biology, Biobank, 03 medical and health sciences, 0302 clinical medicine, Endophenotype, Multiple comparisons problem, Trait, Family history, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract

Dense genotype data and thousands of phenotypes from large biobanks, coupled with increasingly accessible summary association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide scans for disease-trait associations. Compared to traditional regression approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured on the same cohort. We applied BADGERS to two independent datasets for Alzheimer’s disease (AD; N=61,212). Among the polygenic risk scores (PRS) for 1,738 traits in the UK Biobank, we identified 48 significant trait PRSs associated with AD after adjusting for multiple testing. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Further, we identified 41 significant PRSs associated with AD endophenotypes. While family history and high cholesterol were strongly associated with neuropathologies and cognitively-defined AD subgroups, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD.

Published
2018
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24. Is APOE ε4 required for Alzheimer's disease to develop in TREM2 p.R47H variant carriers?

Author

Amanda B. Kuzma, Adam C. Naj, Gerard D. Schellenberg, Rita Guerreiro, Jose Bras, and Tatiana Orme

Subjects
0301 basic medicine, Genetics, Apolipoprotein E, Histology, Membrane Glycoproteins, business.industry, TREM2, Apolipoprotein E4, Disease, Individual risk, Pathology and Forensic Medicine, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Neurology, Alzheimer Disease, Physiology (medical), Medicine, Humans, Neurology (clinical), Allele, Receptors, Immunologic, business, 030217 neurology & neurosurgery
Abstract

Murray and colleagues [1] reported the occurrence of pathologically-confirmed Alzheimer's disease (AD) in cases harbouring the TREM2 p.R47H variant only when APOE e4 alleles were also present. They suggested that the presence of an e4 APOE allele is necessary for the development of AD pathology in TREM2 p.R47H carriers. This is an important hypothesis as it can have significant impact on individual risk assessment and on understanding the mechanisms of disease. This article is protected by copyright. All rights reserved.

Published
2018

25. P4‐044: THE GCAD CLOUD‐BASED WORKFLOW FOR PROCESSING WHOLE EXOME AND WHOLE GENOME DATA FROM THE ALZHEIMER'S DISEASE SEQUENCING PROJECT

Author

William J. Salerno, Yi-Fan Chou, Laura B. Cantwell, Adam C. Naj, John Malamon, Gerard D. Schellenberg, Liming Qu, Otto Valladares, Li-San Wang, Yi Zhao, Han-Jen Lin, Prabhakaran Gangadharan, Yuk Yee Leung, and Amanda B. Kuzma

Subjects
Epidemiology, Computer science, business.industry, Health Policy, Cloud computing, Computational biology, Disease, Genome, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Workflow, Developmental Neuroscience, Neurology (clinical), Geriatrics and Gerontology, business, Exome
Published
2018
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26. P1‐157: NIA GENETICS OF ALZHEIMER'S DISEASE DATA STORAGE SITE (NIAGADS): UPDATE 2018

Author

Briana Vogel, Zivadin Katanic, Christian J. Stoeckert, Adam C. Naj, Prabhakaran Gangadharan, Yi Zhao, Caiyi Zhong, Han-Jen Lin, Gerard D. Schellenberg, Otto Valladares, Liming Qu, Li-San Wang, Emily Greenfest-Allen, Yuk Yee Leung, and Amanda B. Kuzma

Subjects
Genetics, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Disease, Geriatrics and Gerontology, Biology
Published
2018
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27. P3‐130: NIA GENETICS OF ALZHEIMER'S DISEASE DATA STORAGE SITE (NIAGADS): ALZHEIMER'S GENOMICS DATABASE

Author

Liming Qu, Christian J. Stoeckert, Otto Valladares, Emily Greenfest-Allen, Li-San Wang, Yuk Yee Leung, Amanda B. Kuzma, and Prabhakaran Gangadharan

Subjects
Genetics, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Genomics, Neurology (clinical), Disease, Geriatrics and Gerontology, Biology
Published
2018
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28. P1‐149: THE ALZHEIMER'S DISEASE SEQUENCING PROJECT (ADSP) DATA UPDATE 2018

Author

Jason Waligorski, John J. Farrell, Eric Boerwinkle, Yuk Yee Leung, Laura B. Cantwell, Amanda B. Kuzma, Seung Hoan Choi, Sudha Seshadri, Elizabeth L. Appelbaum, Tatiana Foroud, Adam C. Naj, Namrata Gupta, Gerard D. Schellenberg, Kelley Faber, Otto Valladares, Joshua C. Bis, Li-San Wang, Liming Qu, Kara L. Hamilton-Nelson, Anita L. DeStefano, Yi Zhao, Donna M. Muzny, Briana Vogel, Robert S. Fulton, Dolly Reyes-Dumeyer, and William J Salerno

Subjects
Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, business.industry, Health Policy, Medicine, Neurology (clinical), Computational biology, Disease, Geriatrics and Gerontology, business
Published
2018
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29. Quality Control and Integration of Genotypes from Two Calling Pipelines for Whole Genome Sequence Data in the Alzheimer’s Disease Sequencing Project

Author

Gerard D. Schellenberg, Alejandro Q. Nato, Daniel C. Koboldt, Kara L. Hamilton-Nelson, Honghuang Lin, Badri N. Vardarajan, Seung Hoan Choi, Alzheimer’s Disease Sequencing, Harkirat Sohi, Cornelia M. van Duijn, John Malamon, Michael A. Schmidt, Daniel Lancour, Fangui Sun, Simon White, Anita L. DeStefano, William J Salerno, Eden R. Martin, Sven J. van der Lee, Bowen Wang, Josée Dupuis, Joshua C. Bis, Li-San Wang, William S. Bush, Sudha Seshadri, Ellen M. Wijsman, Brian W. Kunkle, Adam C. Naj, Namrata Gupta, Amanda B. Kuzma, Najaf Amin, L. Adrienne Cupples, Mohamad Saad, Eric Boerwinkle, Yiyi Ma, Mariusz Butkiewicz, Neurology, Amsterdam Neuroscience - Neurodegeneration, and Epidemiology

Subjects
0106 biological sciences, Male, Quality Control, Genotype, Genotyping Techniques, Disease, Computational biology, Biology, 01 natural sciences, Article, 03 medical and health sciences, symbols.namesake, Alzheimer Disease, Genetics, Humans, Multiplex, Indel, 030304 developmental biology, Whole genome sequencing, 0303 health sciences, Variant Call Format, Polymorphism, Genetic, Whole Genome Sequencing, Mendelian inheritance, symbols, Female, Algorithms, 010606 plant biology & botany, Genome-Wide Association Study
Abstract

The Alzheimer’s Disease Sequencing Project (ADSP) performed whole genome sequencing (WGS) of 584 subjects from 111 multiplex families at three sequencing centers. Genotype calling of single nucleotide variants (SNVs) and insertion-deletion variants (indels) was performed centrally using GATK-HaplotypeCaller and Atlas V2. The ADSP Quality Control (QC) Working Group applied QC protocols to project-level variant call format files (VCFs) from each pipeline, and developed and implemented a novel protocol, termed “consensus calling,” to combine genotype calls from both pipelines into a single high-quality set. QC was applied to autosomal bi-allelic SNVs and indels, and included pipeline-recommended QC filters, variant-level QC, and sample-level QC. Low-quality variants or genotypes were excluded, and sample outliers were noted. Quality was assessed by examining Mendelian inconsistencies (MIs) among 67 parent-offspring pairs, and MIs were used to establish additional genotype-specific filters for GATK calls. After QC, 578 subjects remained. Pipeline-specific QC excluded ~12.0% of GATK and 14.5% of Atlas SNVs. Between pipelines, ~91% of SNV genotypes across all QCed variants were concordant; 4.23% and 4.56% of genotypes were exclusive to Atlas or GATK, respectively; the remaining ~0.01% of discordant genotypes were excluded. For indels, variant-level QC excluded ~36.8% of GATK and 35.3% of Atlas indels. Between pipelines, ~55.6% of indel genotypes were concordant; while 10.3% and 28.3% were exclusive to Atlas or GATK, respectively; and ~0.29% of discordant genotypes were. The final WGS consensus dataset contains 27,896,774 SNVs and 3,133,926 indels and is publicly available.AbbreviationsAD, Alzheimer’s disease; QC, Quality Control; LSSAC, Large-Scale Sequencing and Analysis Center; Broad, Broad Institute Genomics Service; Baylor, Baylor College of Medicine Human Genome Sequencing Center; WashU, Washington University-St. Louis McDonnell Genome Institute; WGS, whole genome sequencing; WES, whole exome sequencing; indel, insertion-deletion variants; VCF, variant control format; MI, Mendelian inconsistency; MC, Mendelian consistency; GWAS, genome-wide association study; VR, referent allele read depth; DP, overall read depth; MS, mapping score; GQ, genotype quality score; Ti/Tv, Transition/Transversion; CS, concordance code

Published
2018
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30. A statistical framework for cross-tissue transcriptome-wide association analysis

Author

Jiawei Wang, Sydney Muchnik, Amanda B. Kuzma, Yi Zhao, Hongyu Zhao, Yiming Hu, Yu Shi, Shubhabrata Mukherjee, Haoyi Weng, Brian W. Kunkle, Seyedeh M. Zekavat, Adam C. Naj, Qiongshi Lu, Zhaolong Yu, Mo Li, Paul K. Crane, Pradeep Natarajan, and Boyang Li

Subjects
0303 health sciences, Genome-wide association study, Computational biology, Biology, Heritability, Genetic architecture, 03 medical and health sciences, 0302 clinical medicine, Sample size determination, Trait, Gene, 030217 neurology & neurosurgery, Imputation (genetics), 030304 developmental biology, Genetic association
Abstract

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to predict (impute) gene expression levels from genotypes from samples with matched genotypes and expression levels in a specific tissue. However, it is challenging to develop robust and accurate imputation models with limited sample sizes for any single tissue. Here, we first introduce a multi-task learning approach to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average 39% improvement in imputation accuracy and generated effective imputation models for an average 120% (range 13%-339%) more genes in each tissue. We then describe a summary statistic-based testing framework that combines multiple single-tissue associations into a single powerful metric to quantify overall gene-trait association at the organism level. When our method, called UTMOST, was applied to analyze genome wide association results for 50 complex traits (Ntotal=4.5 million), we were able to identify considerably more genes in tissues enriched for trait heritability, and cross-tissue analysis significantly outperformed single-tissue strategies (p=1.7e-8). Finally, we performed a cross-tissue genome-wide association study for late-onset Alzheimer’s disease (LOAD) and replicated our findings in two independent datasets (Ntotal=175,776). In total, we identified 69 significant genes, many of which are novel, leading to novel insights on LOAD etiologies.

Published
2018
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31. A statistical framework for cross-tissue transcriptome-wide association analysis

Author

Sydney Muchnik, Shubhabrata Mukherjee, Amanda B. Kuzma, Seyedeh M. Zekavat, Mo Li, Paul K. Crane, Yiming Hu, Hui Lu, Jiawei Wang, Qiongshi Lu, Haoyi Weng, Boyang Li, Yu Shi, Hongyu Zhao, Brian W. Kunkle, Adam C. Naj, Zhaolong Yu, Jianlei Gu, Yi Zhao, and Pradeep Natarajan

Subjects
0303 health sciences, Genotype, Models, Genetic, Gene Expression Profiling, Gene Expression, Genome-wide association study, Computational biology, Biology, Polymorphism, Single Nucleotide, Genetic architecture, Article, Transcriptome, 03 medical and health sciences, 0302 clinical medicine, Sample size determination, Genetics, Susceptibility locus, Learning methods, Humans, 030217 neurology & neurosurgery, Imputation (genetics), 030304 developmental biology, Genetic association, Genome-Wide Association Study
Abstract

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene-trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies.

Published
2018

32. P1-134: NIA GENETICS OF ALZHEIMER'S DISEASE DATA STORAGE SITE (NIAGADS): ALZHEIMER'S GENOMICS DATABASE - 2019 UPDATE

Author

Emily Greenfest-Allen, Christian J. Stoeckert, Li-San Wang, Conor Klamann, Yuk Yee Leung, Amanda B. Kuzma, Prabhakaran Gangadharan, Liming Qu, and Otto Valladares

Subjects
Genetics, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Genomics, Neurology (clinical), Disease, Geriatrics and Gerontology, Biology
Published
2019
Full Text
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33. P4-094: EXOME-WIDE ANALYSIS IDENTIFIES NOVEL SEX-SPECIFIC CANDIDATE GENES FOR ALZHEIMER DISEASE

Author

Kara L. Hamilton-Nelson, Margaret A. Pericak-Vance, Gerard D. Schellenberg, Li-San Wang, Gary W. Beecham, Melissa Jean-Francois, Eden R. Martin, Lindsay A. Farrer, Jonathan L. Haines, Badri N. Vardarajan, Richard Mayeux, Timothy J. Hohman, William S. Bush, Brian W. Kunkle, Adam C. Naj, Lissette Gomez, Amanda B. Kuzma, and Lily Wang

Subjects
Candidate gene, Epidemiology, Health Policy, Computational biology, Biology, medicine.disease, Sex specific, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, medicine, Neurology (clinical), Geriatrics and Gerontology, Alzheimer's disease, Exome
Published
2019
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34. Genetic Variation in Genes Underlying Diverse Dementias May Explain a Small Proportion of Cases in the Alzheimer's Disease Sequencing Project

Author

William J Salerno, Christiane Reitz, Josée Dupuis, Richard Mayeux, Sudha Seshadri, Badri N. Vardarajan, Gerard D. Schellenberg, Lindsay A. Farrer, Elizabeth E. Blue, Ellen M. Wijsman, Dolly Reyes, Harkirat Sohi, Kathryn L. Lunetta, Yiyi Ma, Otto Valadares, Eden R. Martin, Sandra Barral, Anita L. DeStefano, Carlos Cruchaga, Eric Boerwinkle, Joshua C. Bis, Li-San Wang, Gyungah Jun, Alison Goate, Mariusz Butkiewicz, Jenny Lee, Patrick A. Navas, Margaret A. Pericak-Vance, Michael O. Dorschner, Gary W. Beecham, William S. Bush, Jennifer E. Below, Timothy A. Thornton, Brian W. Kunkle, Alejandro Q. Nato, Adam C. Naj, Jim Jaworski, Amanda B. Kuzma, Debby W. Tsuang, Hiep Nguyen, Cornelia M. van Duijn, Jonathan L. Haines, and Epidemiology

Subjects
Male, 0301 basic medicine, Apolipoprotein E, Cognitive Neuroscience, Nerve Tissue Proteins, Disease, Biology, Polymorphism, Single Nucleotide, Article, Cohort Studies, Novel gene, 03 medical and health sciences, 0302 clinical medicine, Alzheimer Disease, Genetic variation, Prevalence, medicine, PSEN1, Humans, Dementia, Gene, Aged, Aged, 80 and over, Genetics, TREM2, Genetic Variation, Sequence Analysis, DNA, medicine.disease, Psychiatry and Mental health, 030104 developmental biology, Case-Control Studies, Female, Geriatrics and Gerontology, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Background/Aims: The Alzheimer’s Disease Sequencing Project (ADSP) aims to identify novel genes influencing Alzheimer’s disease (AD). Variants within genes known to cause dementias other than AD have previously been associated with AD risk. We describe evidence of co-segregation and associations between variants in dementia genes and clinically diagnosed AD within the ADSP. Methods: We summarize the properties of known pathogenic variants within dementia genes, describe the co-segregation of variants annotated as “pathogenic” in ClinVar and new candidates observed in ADSP families, and test for associations between rare variants in dementia genes in the ADSP case-control study. The participants were clinically evaluated for AD, and they represent European, Caribbean Hispanic, and isolate Dutch populations. Results/Conclusions: Pathogenic variants in dementia genes were predominantly rare and conserved coding changes. Pathogenic variants within ARSA, CSF1R, and GRN were observed, and candidate variants in GRN and CHMP2B were nominated in ADSP families. An independent case-control study provided evidence of an association between variants in TREM2, APOE, ARSA, CSF1R, PSEN1, and MAPT and risk of AD. Variants in genes which cause dementing disorders may influence the clinical diagnosis of AD in a small proportion of cases within the ADSP.

Published
2018

35. Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

Author

John Hardy, Nick C. Fox, Lena Lilius, Christine Van Broeckhoven, Mindy J. Katz, Carlos Cruchaga, Joshua W. Miller, Carol Brayne, Letizia Concari, Christopher Shaw, Minerva M. Carrasquillo, Richard Mayeux, Anne Boland, Charles DeCarli, Helena C. Chui, Laura B. Cantwell, Yoland Aladro Benito, Chuang Kuo Wu, Elaine R. Peskind, Andrew McDavid, M. Ilyas Kamboh, Amanda Smith, Pascual Sánchez-Juan, Jean-François Deleuze, Jayanadra J. Himali, Thomas H. Mosley, Thomas J. Montine, Chuanhai Cao, Andreas J. Forstner, Thomas G. Beach, Robert Barber, Miquel Aguilar, Liming Qu, Jerome I. Rotter, Matthew J. Huentelman, Christiane Reitz, Christopher J. O'Donnell, Steven G. Younkin, Bradley T. Hyman, Bruce L. Miller, Rachelle S. Doody, Eric B. Larson, Ronald L. Hamilton, Todd E. Golde, Steven E. Arnold, Melissa E. Garcia, Rachel Raybould, Lena Kilander, Mark A. Sager, Kevin Morgan, Kathryn L. Lunetta, William Perry, Joseph D. Buxbaum, Craig S. Atwood, Thomas D. Bird, Michael Conlon O'Donovan, Robert Olaso, Juan Fortea, Susanne Moebus, Lisa L. Barnes, Rachel Marshall, Huntington Potter, Mercè Boada, Shahzad Ahmad, Paolo Caffarra, Daniel C. Marson, Jonathan L. Haines, Perrie M. Adams, John M Olichney, Lars Lannfelt, Stefanie Heilmann-Heimbach, Markus M. Nöthen, Shubhabrata Mukherjee, John Malamon, Xue Wang, Christopher S. Carlson, Karen Ritchie, Roger N. Rosenberg, Paul K. Crane, Alexa S. Beiser, Céline Bellenguez, Robert C. Green, Maria Urbano, Petra Proitsi, John Powell, Elisa Majounie, Ammar Al-Chalabi, Hakon Hakonarson, Yogen Patel, Martin Scherer, Julie Williams, Richard B. Lipton, Vincent Dermecourt, Adam L. Boxer, Gerard D. Schellenberg, David G. Clark, Anita L. DeStefano, Joel H. Kramer, Victoria Alvarez, Nandini Badarinarayan, Oscar L. Lopez, Chris Corcoran, Ubaldo Bonuccelli, Donald R. Royall, James Bowen, Monica Diez Fairen, Tricia A. Thornton-Wells, Nilufer Ertekin-Taner, Florence Pasquier, Martin Ingelsson, Yi Zhao, John R. Gilbert, Valentina Escott-Price, Amanda B. Kuzma, Fabienne Garzia, Reinhard Heun, Otto Valladares, Andrew J. Saykin, Sara Ortega-Cubero, Liana G. Apostolova, Henry L. Paulson, John K Kauwe, Imelda Barber, Carolina Ceballos Diaz, Douglas Galasko, M. Arfan Ikram, Lluís Tárraga, Carlo Caltagirone, Joan S. Reisch, Wolfgang Maier, Bruno Vellas, Rebecca Sims, Angela Hodges, Matthew P. Frosch, Isabel Henández, Annakaisa Haapasalo, Thor Aspelund, Håkan Thonberg, Aimee Pierce, Roger L. Albin, Wayne W. Poon, Rebecca Sussams, Amy Braddel, Ranjan Duara, Albert V. Smith, Kirk C. Wilhelmsen, Gianfranco Spalletta, Simon Lovestone, Peter Passmore, Ana Frank-García, Cynthia M. Carlsson, Jade Chapman, Nathan D. Price, Philip L. De Jager, John M. Ringman, Seung Hoan Choi, Nicola Denning, Michael John Owen, Clinton T. Baldwin, Amalia C. Bruni, Denis A. Evans, Rudolph E. Tanzi, Dominique Campion, Laura Fratiglioni, Alberto Lleó, Per Hoffmann, Carole Dufouil, Charlotte Forsell, Alun Meggy, Charlene Thomas, Robert S. Stern, James B. Leverenz, Tatiana Foroud, William W. Seeley, James J. Lah, Brian A. Lawlor, Kenneth B. Fallon, Matthias Riemenschneider, Ryan M. Huebinger, Regina M. Carney, Clinton B. Wright, Didier Hannequin, Deborah Blacker, Anne Kinhult-Ståhlbom, Ekaterina Rogaeva, Andrew P. Lieberman, Bernardino Ghetti, Linda J. Van Eldik, Bernadette McGuinness, Thomas Fairchild, Margaret A. Pericak-Vance, Ashok Raj, Reinhold Schmidt, Ronald C. Petersen, Harald Hampel, María J. Bullido, Steven L. Carroll, Maria Candida Deniz Naranjo, Kathleen A. Welsh-Bohmer, Myriam Fornage, Joseph F. Quinn, Caroline Graff, Claudia L. Satizabal, Patrice L. Whitehead, David Wallon, Christopher Medway, Lindsay A. Farrer, Vilmundur Gudnason, Peter St George-Hyslop, Pau Pastor, Frank Jessen, Erin L. Abner, Johanna Jakobsdottir, Hieab H.H. Adams, Roberta Cecchetti, Walter A. Kukull, Thomas S. Wingo, Michelle K. Lupton, Valur Emilsson, Susan M. McCurry, Simon Mead, Hilkka Soininen, Sandra Weintraub, Amy Gerrish, Lindy E. Harrell, Lina Keller, Jean-Charles Lambert, Denise Harold, Stephen Todd, Wei Gu, Maura Gallo, Najaf Amin, Lenore J. Launer, Eleonora Sacchinelli, Mikko Hiltunen, Cécile Dulary, Eliecer Coto, Xueqiu Jian, Nathalie Fievet, Patrizia Mecocci, Sarah Taylor, Eric Boerwinkle, Maria Serpente, Ronald G. Munger, Ina Giegling, Carlo Masullo, Aoibhinn Lynch, Eliezer Masliah, Anne M. Koivisto, Chang En Yu, Qiong Yang, Benedetta Nacmias, Wayne C. McCormick, Kristelle Brown, Alessio Squassina, Deborah C. Mash, Brian W. Kunkle, Makrina Daniilidou, Alison Goate, David Carrell, Kara L. Hamilton-Nelson, Sandra Barral, Vincent Chouraki, Kristel Sleegers, Frank J. Wolters, Joseph E. Parisi, Iwona Kłoszewska, Ronald C. Kim, Sonia Moreno-Grau, Marina Arcaro, Carmen Muñoz Fernadez, Vernon S. Pankratz, Duane Beekly, Sabrina Pichler, Gislain Septier, Delphine Bacq, Amanda J. Myers, Adam C. Naj, Frank Martiniuk, Sudha Seshadri, Badri N. Vardarajan, Joshua A. Sonnen, M.-Marsel Mesulam, Howard J. Rosen, James T. Becker, Chiara Fenoglio, Ge Li, Alberto Pilotto, Mary Sano, Olivier Hanon, Honghuang Lin, Jean Paul G. Vonsattel, W. T. Longstreth, Daniela Galimberti, David C. Rubinsztein, RoseMarie Brundin, Vilmantas Giedraitis, Christine M. Hulette, Peter Holmans, Martin Dichgans, Maria Vronskaya, Céline Derbois, Michelangelo Mancuso, Constantine G. Lyketsos, Christophe Tzourio, Jacques Epelbaum, Raffaele Maletta, Mariet Allen, Hong-Dong Li, James R. Burke, Rik Vandenberghe, David G. Mann, Bruce M. Psaty, Lawrence S. Honig, Beth A. Dombroski, Erik D. Roberson, Cornelia M. van Duijn, Benjamin Grenier-Boley, Seppo Helisalmi, Jean-François Dartigues, Russell H. Swerdlow, Paola Bossù, Ashley R. Winslow, Elio Scarpini, Lesley Jones, Sebastien Engelborghs, John Q. Trojanowski, Jeffrey Kaye, Jenny Lord, Chiara Cupidi, Janet A. Johnston, Dan Rujescu, Feroze Golamaully, Anne Braae, Rafael Blesa, L. Adrienne Cupples, Dennis W. Dickson, Gail P. Jarvik, David W. Fardo, David H. Cribbs, Michael Gill, Jose Bras, Allan I. Levey, Jennifer Williamson, Rhodri Thomas, John C. Morris, Lei Yu, Debby W. Tsuang, Annette M. Hartmann, John H. Growdon, John Collinge, Claudine Berr, Fernando Rivadeneira, Oliver Peters, Albert Hofman, Frank M. LaFerla, Vivianna M. Van Deerlin, James Uphill, David A. Bennett, Onofre Combarros, Gudny Eiriksdottir, Jeremy D. Burgess, Melanie L. Dunstan, Elizabeth Crocco, Keeley J. Brookes, Robert R. Graham, Lon S. Schneider, Eden R. Martin, Matt Hill, Neill R. Graff-Radford, Joseph T. Hughes, Vincenzo Solfrizzi, Taniesha Morgan, Antonio Ciaramella, Bruno Dubois, Juan C. Troncoso, Paolo Bosco, Jordi Clarimón, Daniel H. Geschwind, Virginia Boccardi, Barry Reisberg, Timothy W. Behrens, Annette L. Fitzpatrick, Salvatore Spina, Alexis Brice, Eileen H. Bigio, Marla Gearing, Jeffrey M. Burns, Carol A. Miller, Marilyn S. Albert, Sven J. van der Lee, Sandro Sorbi, C. Dirk Keene, Daniel Levy, Antonio Daniele, Eric M. Reiman, Paramita Chakrabarty, Oscar Sotolongo-Grau, Helena Schmidt, Francesco Panza, Murray A. Raskind, Rita Guerreiro, Gyungah Jun, Anna Karydas, Markus Leber, Harry V. Vinters, Cory C. Funk, Charles C. White, Jill R. Murrell, Sid E. O'Bryant, Nigel J. Cairns, Josée Dupuis, Ann C. McKee, Julie A. Schneider, Megan L. Grove, Malcolm B. Dick, Bradley F. Boeve, Jennifer A. Brody, Sanjay Asthana, Agustín Ruiz, Stefan Herms, Yuning Chen, David Craig, Neil W. Kowall, Maria Donata Orfei, JoAnn T. Tschanz, Florentino Sanchez Garcia, Manuel Mayhaus, Alfredo Ramirez, James Turton, André G. Uitterlinden, Davide Seripa, Lee-Way Jin, Kelley Faber, Maria C. Norton, Shuo Li, Steven H. Ferris, Steffi G. Riedel-Heller, Joshua C. Bis, Li-San Wang, Johannes Kornhuber, Peter Paul De Deyn, Martin R. Farlow, Randall L. Woltjer, Gary W. Beecham, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Hospital of the University of Pennsylvania (HUP), Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia], Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Icelandic Heart Association [Kopavogur, Iceland] (IHA), John P. Hussman Institute for Human Genomics [Miami, FL, USA], University of Miami [Coral Gables], Institut de Biologie François JACOB (JACOB), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Department of Medicine, University of Washington [Seattle], Dr. John T. Macdonald Foundation [Miami, FL, USA] (Department of Human Genetics), Epidémiologie des maladies chroniques : impact des interactions gène environnement sur la santé des populations, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Droit et Santé, Department of Genomics [Bonn, Germany] (Institute of Human Genetics), University of Bonn-Institute of Human Genetics [Bonn, Germany], Department of Molecular Genetics, Institut Català de Neurociències Aplicades [Barcelona, Spain], Well Advanced Solutions, Centre National de Génotypage (CNG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Translational Centre for Regenerative Medicine (TRM), Department of Cell Therapy, Universität Leipzig [Leipzig]-Universität Leipzig [Leipzig], The University of Texas Health Science Center at Houston (UTHealth), Columbia University [New York], University of Eastern Finland, Life & Brain Center - Department of Genomics, Rheinische Friedrich-Wilhelms-Universität Bonn, Génétique, Reproduction et Développement (GReD), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de la Santé et de la Recherche Médicale (INSERM), John P. Hussman Institute for Human Genomics, Neurobiologie de la Croissance et de la Senescence, Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Emmy Noether Project (SFB 833), Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen, Boston University [Boston] (BU), Department of Genomics, Institute for Systems Biology [Seattle, WA, USA], Universitätsklinikum Bonn (UKB), Centre of Excellence for Robotic Vision [Canberra], Australian Research Council [Canberra] (ARC), Neuroscience and Mental Health Research Institute [Cardiff, UK] (School of Medicine), Boston University School of Medicine (BUSM), Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, University of Pennsylvania [Philadelphia], Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Department of Epidemiology and Biostatistics, ERASMUS, Hospital Universitario Doctor Negrín [Las Palmas de Gran Canaria, Spain], Department of Neurodegenerative Diseases, University of Mississippi Medical Center (UMMC), Pathology and Laboratory Medicine [Philadelphia, PA, USA] (Penn Neurodegeneration Genomics Center), UNIROUEN - UFR Santé (UNIROUEN UFR Santé), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Génétique du cancer et des maladies neuropsychiatriques (GMFC), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bioinformatics, GlaxoSmithKline, Aging Research Center [Karolinska Institutet] (ARC ), Stockholm University-Karolinska Institutet [Stockholm], University of Nottingham, UK (UON), University of Texas Health Science Center, Department of Neurobiology, Caring Sciences and Society (NVS), University of Bari Aldo Moro (UNIBA), Ageing Group, Centre for Public Health, Queen's University [Belfast] (QUB), Mayo Clinic [Jacksonville], Maurice Wohl Clinical Neuroscience Institut, King‘s College London, Istituto di Ricovero e Cura a Carattere Scientifico, Ospedale Casa Sollievo della Sofferenza [San Giovanni Rotondo] (IRCCS), Università degli Studi di Perugia (UNIPG), Framingham Heart Study, Boston University [Boston] (BU)-National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), CHU Rouen, Normandie Université (NU), Universidad Autonoma de Madrid (UAM), Centro de Investigacion Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III [Madrid] (ISC), National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), University of Florida [Gainesville] (UF), University of Parma = Università degli studi di Parma [Parme, Italie], Center for Cognitive Disorders AUSL [Parma, Italy], School of Public Health [Boston], Uppsala University, Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Université Pierre et Marie Curie - Paris 6 (UPMC), National Institute on Aging [Bethesda, USA] (NIA), National Institutes of Health [Bethesda] (NIH), Xi'an Jiaotong University (Xjtu), Department of Public health and Caring Sciences, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden, Institute of Gerontology and Geriatrics, Troubles cognitifs dégénératifs et vasculaires - U 1171 (TCDV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Geriatric Medicine and Metabolic Diseases, Departments of Nuclear Medicine, University Medical Centre Hamburg-Eppendorf [Hamburg, Germany], University of Texas Southwestern Medical Center [Dallas], University of Cologne, Laboratoire d'Etudes et de Recherche en Informatique d'Angers (LERIA), Université d'Angers (UA), Johns Hopkins University (JHU), Universität Leipzig [Leipzig], University of Iceland [Reykjavik], Metacohorts Consortium, Harvard School of Public Health, Catholic University of Rome, Medical University Graz, Baylor College of Medicine (BCM), Baylor University, University of North Texas Health Science Center [Fort Worth], Santa Lucia Foundation (IRCCS), Nextel S.A. [Bilbao], Massachusetts General Hospital [Boston], Department of Pathology and Laboratory Medicine and Indiana Alzheimer disease Center, Indiana University School of Medicine, Indiana University System-Indiana University System, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), Beijing University of Technology, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Saul B. Korey Department of Neurology, Albert Einstein College of Medicine [New York]-Yeshiva University, Utah State University (USU), Fundació per la Recerca Biomèdica i Social Mútua Terrassa [Barcelona, Spain], Hospital Universitario Mutua de Terrassa, Département de neurologie [Montpellier], Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [Montpellier]-Université de Montpellier (UM), Department of neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland, Department of neurology, University of Eastern Finland-University Hospital of Kuopio-University of Eastern Finland-University Hospital of Kuopio, Medical University of Łódź (MUL), University of Leicester, MRC Prion Unit, Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, University of Milan, Fondazione Istituto di Ricerca e Cura Carattere Scientifico [Rome], Università degli Studi di Roma Tor Vergata [Roma], Saarland University Hospital, Universitat Autònoma de Barcelona (UAB), Regional Neurogenetic Centre [Lamezia Terme, Italy] (CRN - ASP Catanzaro), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Universidade do Porto, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Experimental and Clinical Pharmacology, St. James Hospital and Trinity College [Dublin, Ireland], School of Medicine [Dublin], Trinity College Dublin, University of Sheffield [Sheffield], Lancaster University, University of Michigan [Ann Arbor], University of Michigan System, David Geffen School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California-University of California, University of Wisconsin-Madison, Rush Alzheimer Disease Center [Chicago, IL, États-Unis], Rush University Medical Center [Chicago], Institute for Advanced Biosciences / Institut pour l'Avancée des Biosciences (Grenoble) (IAB), Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), School of Engineering [Cardiff], Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), Northwestern University Feinberg School of Medicine, Mayo Clinic [Rochester], Swedish Medical Center [Seattle, WA, USA], University of California [San Francisco] (UCSF), University of California, Duke University [Durham], University of Kansas Medical Center [Lawrence], Laboratory of Molecular Neuropsychiatry, Icahn School of Medicine at Mount Sinai [New York] (MSSM), Washington University in Saint Louis (WUSTL), University of South Florida [Tampa] (USF), Fred Hutchinson Cancer Research Center [Seattle] (FHCRC), Medical University of South Carolina [Charleston] (MUSC), University of Southern California (USC), Los Alamos National Laboratory (LANL), Centre de biologie du développement (CBD), Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre de Biologie Intégrative (CBI), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Neurology Department, University of California, Davis (UCDavis-Neuro), University of California [Davis] (UC Davis), University of California [Irvine] (UCI), Mount Sinai Medical Center, Indiana State University, University of Alabama at Birmingham [ Birmingham] (UAB), University of Kentucky, New York University [New York] (NYU), NYU System (NYU), Department of Medical and Molecular Genetics, Department of Epidemiology and biostatistics, VU University Medical Center [Amsterdam], Emory University [Atlanta, GA], Department of Neurology, University of California-University of California-David Geffen School of Medicine [Los Angeles], Brigham & Women’s Hospital [Boston] (BWH), Harvard Medical School [Boston] (HMS), Department of Medical Genetics, HMNC Brain Health, Alzheimer Disease Research Laboratory, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Oregon Health and Science University [Portland] (OHSU), Cleveland Clinic, Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Department of Psychiatry, School of Medicine-Johns Hopkins University and Johns Hopkins Bayview Medical Center, Douglas Mental Health University Institute [Montréal], McGill University = Université McGill [Montréal, Canada], Department of neurosciences, University of California [San Diego] (UC San Diego), Department of Physics and Astronomy [Fort Worth], Texas Christian University (TCU), Department of Computer Science [University of California, Davis], Indiana University System, Institute for Aging and Alzheimer’s Disease Research [Fort Worth] (IAADR), Department of Laboratory Medicine and Pathology, Mayo Clinic, Institute for Memory Impairments and Neurological Disorders [Irvine], University of Colorado Anschutz [Aurora], Tanz Center Research in Neurodegenerative Diseases [Toronto], University of Toronto, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Keck School of Medicine [Los Angeles], Indiana University [South Bend], Massachusetts General Hospital, Novartis Institutes for Biomedical Research [Cambridge, MA, USA], Departments of Pathology and Laboratory Medicine (Neuropathology) and Neurology, UCLA Medical Center-David Geffen School of Medicine [Los Angeles], University of California-University of California-University of California [Los Angeles] (UCLA), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Institut de Génomique d'Evry (IG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, University of Antwerp (UA), Institute Born-Bunge, Karolinska Institutet [Stockholm], Karolinska University Hospital [Stockholm], University of Kuopio, Centre Mémoire de Ressources et de Recherche [Lille-Bailleul] (CMRR), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Hôpital Roger Salengro [Lille], Laboratoire d'Analyse Génomique, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Inserm-U1167, Dpt Gériatrie [CHU Broca], AP-HP - Hôpital Cochin Broca Hôtel Dieu [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Neuroépidémiologie, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC), Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 AMP), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Department of Epidemiology, University of Washington, School of Medicine [Los Angeles], Albert Einstein College of Medicine [New York], IdiPAZ - Instituto de Investigación La Paz [Madrid, Spain], Instituto de Física Teórica UAM/CSIC (IFT), Universidad Autonoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Department of Internal Medicine, University of Central Asturias [Oviedo, Spain], Human Genome Sequencing Center, Baylor College of Medicine, Baylor University-Baylor University, Department of Epidemiology, Erasmus Medical Centre, Translational Genomics Research Institute [Phoenix, AZ, USA], University of Arizona, Banner Alzheimer's Institute [Phoenix, AZ, États-Unis], University of Texas Health Science Center at San Antonio [San Antonio], Mount Sinai School of Medicine, Department of Psychiatry-Icahn School of Medicine at Mount Sinai [New York] (MSSM), Department. of Neurological Sciences, University of Milan, IRCCS Ospedale Maggiore Policlinico, Centre for Research in Neurodegenerative Diseases, VA Puget Sound Health Care System/GRECC [Seattle, WA, USA], University of Pisa - Università di Pisa, Pfizer Worldwide Research and Development [Cambridge, MA, USA], Università cattolica del Sacro Cuore [Piacenza e Cremona] (Unicatt), Texas Tech University Health Sciences Center, Texas Tech University [Lubbock] (TTU), Saarland University [Saarbrücken], University of Bonn, Department of Public Health and Primary Care, University of Cambridge [UK] (CAM), Cambridge Institute for Medical Research (CIMR), Department of Molecular Neurosciences, Institute of Neurology, UCL, Institute of Psychiatry, Institute of psychiatry, University of British Columbia (UBC), the Clinical Neuroscience Research Group, University of Manchester [Manchester]-Greater Manchester Neurosciences Centre, Aristotle University of Thessaloniki, Memory and Dementia Centre, 3rd Department of Neurology, G. Pa, University of Barcelona, University of Southampton, Department of Psychiatry [Oxford] (POWIC), University of Oxford [Oxford]-The Warneford Hospital, School of Psychology [Cardiff University], Department of Medical Sciences, UCL, Institute of Neurology [London], Washington University School of Medicine, Netherlands Genomics Initiative, Netherlands Consortium for Healthy Aging [Leiden, Netherlands] (NCHA), School of Medecine, Center for Translational and Computational Neuroimmunology [New York, NY, États-Unis] (CTCN), Department of Neurology [New York, NY, États-Unis], Columbia University Medical Center (CUMC), Columbia University [New York]-Columbia University [New York]-Columbia University Medical Center (CUMC), Columbia University [New York]-Columbia University [New York], School of Life Sciences, Department of Neuroscience, Mayo Clinic Jacksonville, Icelandic Heart Association, Heart Preventive Clinic and Research Institute, Klinik für Psychiatrie, Martin-Luther-University Halle-Wittenberg, Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), The Center for Applied Genomics, Children’s Hospital of Philadelphia (CHOP ), Clínica Universidad de Navarra [Pamplona], Neurodegenerative Brain Diseases Group, VIB, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University-Medical Research Council, Brigham Young University (BYU), Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, The Gertrude H Sergivesky Center, Columbia University College of Physicians and Surgeons, Genetic Epidemiology Unit, Section of Clinical and Molecular Neurogenetics, Universität zu Lübeck [Lübeck], University of Pennsylvania - Department of Pathology & Laboratory Medecine, Framingham Heart Study [Framingham, MA, USA], ANR-10-IAHU-0006,IHU-A-ICM,Institut de Neurosciences Translationnelles de Paris(2010), European Project: 29845,LSH-ACC-MENTOR, University of Pennsylvania-University of Pennsylvania, Universität Bonn = University of Bonn-Institute of Human Genetics [Bonn, Germany], Universität Leipzig-Universität Leipzig, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania, Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA), Università degli Studi di Perugia = University of Perugia (UNIPG), Universidad Autónoma de Madrid (UAM), Università degli studi di Parma = University of Parma (UNIPR), Institut de la Mémoire et de la Maladie d'Alzheimer [CHU Pitié-Salpétriêre] (IM2A), Université Pierre et Marie Curie - Paris 6 (UPMC)-CHU Pitié-Salpêtrière [AP-HP], Troubles cognitifs dégénératifs et vasculaires - U 1171 - EA 1046 (TCDV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Droit et Santé-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Universität Leipzig, Università cattolica del Sacro Cuore = Catholic University of the Sacred Heart [Roma] (Unicatt), Yeshiva University- Albert Einstein College of Medicine [New York], Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [CHU Montpellier], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Université de Montpellier (UM), Università degli Studi di Milano = University of Milan (UNIMI), Saarland University Hospital (UKS), Università degli Studi di Firenze = University of Florence (UniFI), Universidade do Porto = University of Porto, University of California (UC)-University of California (UC), University of California [San Francisco] (UC San Francisco), University of California (UC), University of Kansas Medical Center [Kansas City, KS, USA], Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), University of California [Irvine] (UC Irvine), University of Kentucky (UK), University of California (UC)-University of California (UC)-David Geffen School of Medicine [Los Angeles], Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California (UC)-University of California (UC)-University of California [Los Angeles] (UCLA), Université Paris-Saclay-Institut de Biologie François JACOB (JACOB), Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Groupe de recherche clinique Alzheimer Precision Medicine (GRC 21 - APM), Sorbonne Université (SU), Universidad Autónoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), University of Texas Health Science Center at San Antonio [San Antonio, Tx, USA], Universität Bonn = University of Bonn, University of Oxford-The Warneford Hospital, Medical Research Council-Cardiff University, Universität zu Lübeck = University of Lübeck [Lübeck], Epidemiology, Neurology, Gastroenterology & Hepatology, Internal Medicine, Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement (Inserm U1167 - RID-AGE - Institut Pasteur), Génétique, Reproduction et Développement - Clermont Auvergne (GReD), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), Eberhard Karls Universität Tübingen, IRCCS 'Casa Sollievo della Sofferenza', Centro de Investigación Biomédica en Red para Enfermedades Neurodegenerativas (Ciberned), University of Florida [Gainesville], University of Parma, Troubles cognitifs dégénératifs et vasculaires (U1171), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-INSERM, Yeshiva University- Albert Einstein College of Medicine, Institut d’Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520 (IEMN), Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Université Polytechnique Hauts-de-France (UPHF)-Ecole Centrale de Lille-Université Polytechnique Hauts-de-France (UPHF)-Institut supérieur de l'électronique et du numérique (ISEN), Autonomous University of Barcelona (UAB), Università degli Studi di Firenze [Firenze], Universidade do Porto [Porto], Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Washington University in St Louis, University of South Florida (USF), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, McGill University, Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Centre National de la Recherche Scientifique (CNRS), Neuropsychiatrie : recherche épidémiologique et clinique, Alzheimer Precision Medicine GRC n°21 (APM), CHU Pitié-Salpêtrière [APHP], Albert Einstein College of Medicine, Universidad Autonoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Università Cattolica del S. Cuore - Catholic University of the Sacred Hearth, University of Florence (UNIFI), CIBER de Enfermedades Neurodegenerativas (CIBERNED), Universität zu Lübeck [Lübeck] - University of Lübeck [Lübeck], [ANR-10-IAIHU-06],« Investissements d'avenir » ,Agence nationale de la recherche (ANR), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Icahn School of Medicine at Mount Sinai [New York] (MSSM)-Department of Psychiatry, van der Lee, Sven J [0000-0003-1606-8643], Naj, Adam C [0000-0002-9621-2942], Badarinarayan, Nandini [0000-0002-6944-748X], Chouraki, Vincent [0000-0002-4698-1794], Graham, Robert R [0000-0001-7151-4277], Hoffmann, Per [0000-0002-6573-983X], Smith, Albert V [0000-0003-1942-5845], Satizabal, Claudia L [0000-0002-1115-4430], Brody, Jennifer A [0000-0001-8509-148X], Wolters, Frank J [0000-0003-2226-4050], Lupton, Michelle K [0000-0002-7274-7299], Lin, Honghuang [0000-0003-3043-3942], Adams, Hieab H [0000-0003-3687-2508], Giedraitis, Vilmantas [0000-0003-3423-2021], Pasquier, Florence [0000-0001-9880-9788], Chen, Yuning [0000-0002-7358-7055], Bossù, Paola [0000-0002-1432-0078], Ghetti, Bernardino [0000-0002-1842-8019], Yang, Qiong [0000-0002-3658-1375], Aspelund, Thor [0000-0002-7998-5433], Bullido, María J [0000-0002-6477-1117], Rivadeneira, Fernando [0000-0001-9435-9441], Rubinsztein, David C [0000-0001-5002-5263], Al-Chalabi, Ammar [0000-0002-4924-7712], Tsolaki, Magda [0000-0002-2072-8010], De Jager, Philip L [0000-0002-8057-2505], Dickson, Dennis W [0000-0001-7189-7917], Van Broeckhoven, Christine [0000-0003-0183-7665], Ikram, M Arfan [0000-0003-0372-8585], Amouyel, Philippe [0000-0001-9088-234X], Lambert, Jean-Charles [0000-0003-0829-7817], Apollo - University of Cambridge Repository, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 APM), Berr, Claudine, Institut de Neurosciences Translationnelles de Paris - - IHU-A-ICM2010 - ANR-10-IAHU-0006 - IAHU - VALID, and Mentoring of LifeSciHealth-Multipliers in the Accession Candidate Countries - LSH-ACC-MENTOR - 29845 - OLD

Subjects
0301 basic medicine, Linkage disequilibrium, [SDV]Life Sciences [q-bio], Medizin, Sequence Homology, Genome-wide association study, genetics [Alzheimer Disease], metabolism [Microglia], Linkage Disequilibrium, 0302 clinical medicine, genetics [Protein Interaction Maps], genetics [Membrane Glycoproteins], Gene Frequency, Immunologic, genetics [Adaptor Proteins, Signal Transducing], Receptors, genetics [Exome], Odds Ratio, Innate, genetics [Receptors, Immunologic], Exome, Protein Interaction Maps, genetics [Genetic Predisposition to Disease], Receptors, Immunologic, ABI3 protein, human, Genetics, Adaptor Proteins, Signal Transducing, Alzheimer Disease, Amino Acid Sequence, Case-Control Studies, Gene Expression Profiling, Genetic Predisposition to Disease, Genotype, Humans, Immunity, Innate, Membrane Glycoproteins, Microglia, Phospholipase C gamma, Sequence Homology, Amino Acid, Polymorphism, Single Nucleotide, Adaptor Proteins, Single Nucleotide, 3. Good health, [SDV] Life Sciences [q-bio], Amino Acid, Settore MED/26 - NEUROLOGIA, genetics [Phospholipase C gamma], [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Alzheimer's disease, Common disease-common variant, Biology, Article, 03 medical and health sciences, ddc:570, medicine, Journal Article, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Polymorphism, Allele frequency, TREM2 protein, human, TREM2, Case-control study, Signal Transducing, Immunity, medicine.disease, R1, Minor allele frequency, genetics [Immunity, Innate], 030104 developmental biology, Human medicine, 030217 neurology & neurosurgery
Abstract

International audience; We identified rare coding variants associated with Alzheimer's disease in a three-stage case-control study of 85,133 subjects. In stage 1, we genotyped 34,174 samples using a whole-exome microarray. In stage 2, we tested associated variants (P < 1 × 10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, we used an additional 14,997 samples to test the most significant stage 2 associations (P < 5 × 10-8) using imputed genotypes. We observed three new genome-wide significant nonsynonymous variants associated with Alzheimer's disease: a protective variant in PLCG2 (rs72824905: p.Pro522Arg, P = 5.38 × 10-10, odds ratio (OR) = 0.68, minor allele frequency (MAF)cases = 0.0059, MAFcontrols = 0.0093), a risk variant in ABI3 (rs616338: p.Ser209Phe, P = 4.56 × 10-10, OR = 1.43, MAFcases = 0.011, MAFcontrols = 0.008), and a new genome-wide significant variant in TREM2 (rs143332484: p.Arg62His, P = 1.55 × 10-14, OR = 1.67, MAFcases = 0.0143, MAFcontrols = 0.0089), a known susceptibility gene for Alzheimer's disease. These protein-altering changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified risk genes in Alzheimer's disease. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to the development of Alzheimer's disease.

Published
2017
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36. [P3–090]: THE ALZHEIMER's DISEASE SEQUENCING PROJECT (ADSP) DATA UPDATE 2017

Author

Rebecca Cweibel, Elizabeth L. Appelbaum, John J. Farrell, Robert S. Fulton, Otto Valladares, Sudha Seshadri, Eric Boerwinkle, Laura B. Cantwell, Tatiana Foroud, Adam C. Naj, Seung Hoan Choi, Namrata Gupta, Liming Qu, Jason Waligorski, Mike Feolo, Gerard D. Schellenberg, Kara L. Hamilton-Nelson, Yuk Yee Leung, Amanda B. Kuzma, Anita L. DeStefano, Han-Jen Lin, Adam Stine, Dolly Reyes-Dumeyer, William J Salerno, Donna M. Muzny, Joshua C. Bis, Li-San Wang, and Kelley Faber

Subjects
Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, business.industry, Health Policy, Medicine, Neurology (clinical), Computational biology, Disease, Geriatrics and Gerontology, business
Published
2017
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37. [P3–097]: NIA GENETICS OF ALZHEIMER's DISEASE DATA STORAGE SITE (NIAGADS): 2017

Author

Emily Greenfest-Allen, Daniel Micah Childress, Adam C. Naj, Otto Valladares, Liming Qu, Prabhakaran Gangadharan, Han-Jen Lin, Christian J. Stoeckert, Li-San Wang, Rebecca Cweibel, Gerard D. Schellenberg, Yuk Yee Leung, and Amanda B. Kuzma

Subjects
Genetics, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Disease, Geriatrics and Gerontology, Biology
Published
2017
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38. [O2–08–02]: SEX‐SPECIFIC ANALYSIS OF THE ADSP CASE‐CONTROL WHOLE‐EXOME SEQUENCING DATASET

Author

Margaret A. Pericak-Vance, Brian W. Kunkle, Adam C. Naj, Li-San Wang, Gary W. Beecham, Kara L. Hamilton-Nelson, Eden R. Martin, Yiyi Ma, Dan Lancour, Mariusz Butkiewicz, John Malamon, Jonathan L. Haines, Gerard D. Schellenberg, Lindsay A. Farrer, Richard Mayeux, William S. Bush, John J. Farrell, and Amanda B. Kuzma

Subjects
Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Computational biology, Geriatrics and Gerontology, Biology, Sex specific, Exome sequencing
Published
2017
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39. [O1–03–01]: GENOME‐WIDE RARE VARIANT IMPUTATION AND TISSUE‐SPECIFIC TRANSCRIPTOMIC ANALYSIS IDENTIFY NOVEL RARE VARIANT CANDIDATE LOCI IN LATE‐ONSET ALZHEIMER's DISEASE: THE ALZHEIMER's DISEASE GENETICS CONSORTIUM

Author

Amanda B. Kuzma, Brian W. Kunkle, Hung-Hsin Chen, Adam C. Naj, Yi Zhao, Gerard D. Schellenberg, Margaret A. Pericak-Vance, Christiane Reitz, Jonathan L. Haines, Li-San Wang, Richard Mayeux, Jennifer E. Below, Gary W. Beecham, Lindsay A. Farrer, Eden R. Martin, Lauren E. Petty, Sven J. van der Lee, Kara L. Hamilton-Nelson, and Otto Valladares

Subjects
0301 basic medicine, Genetics, Epidemiology, Health Policy, Late onset, Disease, Biology, Genome, Transcriptome, 03 medical and health sciences, Psychiatry and Mental health, Cellular and Molecular Neuroscience, 030104 developmental biology, 0302 clinical medicine, Developmental Neuroscience, Tissue specific, Neurology (clinical), Geriatrics and Gerontology, 030217 neurology & neurosurgery, Imputation (genetics)
Published
2017
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40. O2-10-06: GENOME-WIDE META-ANALYSIS OF LATE-ONSET ALZHEIMER'S DISEASE USING RARE VARIANT IMPUTATION IN 64,859 SUBJECTS IDENTIFIES RISK LOCI WITH ROLES IN INNATE IMMUNITY AND CARDIOVASCULAR TRAITS: THE INTERNATIONAL GENOMICS OF ALZHEIMER'S PROJECT (IGAP)

Author

Céline Bellenguez, Markus Leber, Sudha Seshadri, Benjamin Grenier-Boley, Joshua C. Bis, Li-San Wang, Philippe Amouyel, Jean-Charles Lambert, Alfredo Ramirez, Gerard D. Schellenberg, Josée Dupuis, Yuning Chen, Amanda B. Kuzma, Cornelia M. van Duijn, Jin Sha, Vincent Chouraki, Margaret A. Pericak-Vance, Anita L. DeStefano, Aura Frizzati, Ganna Leonenko, Rebecca Sims, Julie Williams, Jonathan L. Haines, Peter Holmans, Brian W. Kunkle, Adam C. Naj, Hata Karamujić-Čomić, Sven J. van der Lee, Lindsay A. Farrer, and Yi Zhao

Subjects
Genetics, Innate immune system, Epidemiology, Health Policy, Genomics, Late onset, Disease, Biology, Genome, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Meta-analysis, Neurology (clinical), Geriatrics and Gerontology, Imputation (genetics)
Published
2019
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41. P2-151: THE ALZHEIMER'S DISEASE SEQUENCING PROJECT - FOLLOW UP STUDY (ADSP-FUS): INCREASING ETHNIC DIVERSITY IN ALZHEIMER'S GENETICS RESEARCH

Author

Dolly Reyes-Dumeyer, Margaret A. Pericak-Vance, Larry D. Adams, Gerard D. Schellenberg, Kelley Faber, Clifton L. Dalgard, Brian W. Kunkle, Li-San Wang, Adam C. Naj, Jeffery M. Vance, Katrina Celis, Badri N. Vardarajan, Pedro Ramon Mena, Tatiana Foroud, Michael L. Cuccaro, Amanda B. Kuzma, Eden R. Martin, and Richard Mayeux

Subjects
Gerontology, Epidemiology, business.industry, Health Policy, Follow up studies, Disease, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Cultural diversity, Medicine, Neurology (clinical), Geriatrics and Gerontology, business
Published
2019
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42. P4-090: NIA GENETICS OF ALZHEIMER'S DISEASE DATA STORAGE SITE (NIAGADS): UPDATE 2019

Author

Emily Greenfest-Allen, Yi Zhao, Otto Valladares, Han-Jen Lin, Zivadin Katanic, Heather Issen, Li-San Wang, Gerard D. Schellenberg, Yuk Yee Leung, Briana Vogel, Amanda B. Kuzma, Michelle K. Moon, Christian J. Stoeckert, Liming Qu, Conor Klamann, Adam C. Naj, and Prabhakaran Gangadharan

Subjects
Genetics, Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Disease, Geriatrics and Gerontology, Biology
Published
2019
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43. VCPA: genomic variant calling pipeline and data management tool for Alzheimer’s Disease Sequencing Project

Author

Laura B. Cantwell, Alzheimer’s Disease Sequencing, Yi-Fan Chou, Otto Valladares, Li-San Wang, Gerard D. Schellenberg, Prabhakaran Gangadharan, Liming Qu, Han-Jen Lin, Yuk Yee Leung, Amanda B. Kuzma, and William J Salerno

Subjects
0301 basic medicine, Statistics and Probability, Source code, Computer science, Data management, media_common.quotation_subject, 0206 medical engineering, Genomics, 02 engineering and technology, computer.software_genre, Genome, Biochemistry, 03 medical and health sciences, 0302 clinical medicine, Alzheimer Disease, Humans, Indel, Molecular Biology, Exome sequencing, Data Management, media_common, 030304 developmental biology, 0303 health sciences, Database, business.industry, Process (computing), High-Throughput Nucleotide Sequencing, Applications Notes, Pipeline (software), Computer Science Applications, Computational Mathematics, 030104 developmental biology, Computational Theory and Mathematics, 030220 oncology & carcinogenesis, Corrigendum, business, Sequence Analysis, computer, Software, 020602 bioinformatics, 030217 neurology & neurosurgery
Abstract

Summary: We report VCPA, our SNP/Indel Variant Calling Pipeline and data management tool used for analysis of whole genome and exome sequencing (WGS/WES) for the Alzheimer’s Disease Sequencing Project. VCPA consists of two independent but linkable components: pipeline and tracking database. The pipeline is coded in Workflow Description Language and is fully optimized for the Amazon elastic compute cloud environment. This includes steps for processing raw sequence reads including read alignment, and all the way up to variant calling using GATK. The tracking database allows users to dynamically view the statuses of jobs running and the quality metrics reported by the pipeline. Users can thus monitor the production process and diagnose if any problem arises during the procedure. All quality metrics (>100 collected per processed genome) are stored in the database, thus facilitating users to compare, share and visualize the results. To summarize, VCPA is functional equivalent to the CCDG/TOPMed pipeline. Together with the dockerized database (also available as Amazon Machine Image), users can easily process any WGS/WES data on Amazon cloud with minimal installation.Availability: VCPA is released under the MIT license and is available for academic and nonprofit use for free. The pipeline source code and step-by-step instructions are available from the National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (http://www.niagads.org/VCPA).Contact:yyee@pennmedicine.upenn.edu or lswang@pennmedicine.upenn.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Published
2019
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44. Apolipoprotein E Genotype and Sex Risk Factors for Alzheimer Disease: A Meta-analysis

Author

Amanda B. Kuzma, Scott C. Neu, Ana Espinosa, Daniele Orlandi, Judy Pa, Duane Beekly, Alberto Redolfi, Wen Chuin Hsu, Stephen P. Arneric, Jiun-Jie Wang, Sanford Auerbach, Li-San Wang, Mercè Boada, Agustín Ruiz, Rebecca L. Koscik, Prabhakaran Gangadharan, Klaus Romero, Yao Liang Chen, Sterling C. Johnson, Giovanni B. Frisoni, Sherral Devine, Arthur W. Toga, Walter A. Kukull, and Rhoda Au

Subjects
0301 basic medicine, Apolipoprotein E, Gerontology, Male, Genotype, Databases, Factual, Logistic regression, Article, 03 medical and health sciences, ddc:616.89, Databases, Sex Factors, 0302 clinical medicine, Apolipoproteins E, Alzheimer Disease, Risk Factors, Factual/statistics & numerical data, 80 and over, Humans, Aged, Aged, 80 and over, Sex Characteristics, Case-control study, Odds ratio, Middle Aged, Confidence interval, Alzheimer Disease/epidemiology/genetics, 030104 developmental biology, Logistic Models, Meta-analysis, Case-Control Studies, lipids (amino acids, peptides, and proteins), Female, Neurology (clinical), Psychology, Apolipoproteins E/genetics, 030217 neurology & neurosurgery, Sex characteristics, Demography
Abstract

Importance It is unclear whether female carriers of the apolipoprotein E (APOE) e4 allele are at greater risk of developing Alzheimer disease (AD) than men, and the sex-dependent association of mild cognitive impairment (MCI) and APOE has not been established. Objective To determine how sex and APOE genotype affect the risks for developing MCI and AD. Data Sources Twenty-seven independent research studies in the Global Alzheimer’s Association Interactive Network with data on nearly 58 000 participants. Study Selection Non-Hispanic white individuals with clinical diagnostic and APOE genotype data. Data Extraction and Synthesis Homogeneous data sets were pooled in case-control analyses, and logistic regression models were used to compute risks. Main Outcomes and Measures Age-adjusted odds ratios (ORs) and 95% confidence intervals for developing MCI and AD were calculated for men and women across APOE genotypes. Results Participants were men and women between ages 55 and 85 years. Across data sets most participants were white, and for many participants, racial/ethnic information was either not collected or not known. Men (OR, 3.09; 95% CI, 2.79-3.42) and women (OR, 3.31; CI, 3.03-3.61) with the APOE e3/e4 genotype from ages 55 to 85 years did not show a difference in AD risk; however, women had an increased risk compared with men between the ages of 65 and 75 years (women, OR, 4.37; 95% CI, 3.82-5.00; men, OR, 3.14; 95% CI, 2.68-3.67; P = .002). Men with APOE e3/e4 had an increased risk of AD compared with men with APOE e3/e3. The APOE e2/e3 genotype conferred a protective effect on women (OR, 0.51; 95% CI, 0.43-0.61) decreasing their risk of AD more ( P value = .01) than men (OR, 0.71; 95% CI, 0.60-0.85). There was no difference between men with APOE e3/e4 (OR, 1.55; 95% CI, 1.36-1.76) and women (OR, 1.60; 95% CI, 1.43-1.81) in their risk of developing MCI between the ages of 55 and 85 years, but women had an increased risk between 55 and 70 years (women, OR, 1.43; 95% CI, 1.19-1.73; men, OR, 1.07; 95% CI, 0.87-1.30; P = .05). There were no significant differences between men and women in their risks for converting from MCI to AD between the ages of 55 and 85 years. Individuals with APOE e4/e4 showed increased risks vs individuals with e3/e4, but no significant differences between men and women with e4/e4 were seen. Conclusions and Relevance Contrary to long-standing views, men and women with the APOE e3/e4 genotype have nearly the same odds of developing AD from age 55 to 85 years, but women have an increased risk at younger ages.

Published
2017

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