Background

An initiative in response to the National Alzheimer’s Project Act (NAPA) has been working towards new biological insights and cures for Alzheimer’s Disease (AD) since its introduction by NIH on February 7, 2012. Aptly named the Alzheimer’s Disease Sequencing Project (ADSP), the project is sequencing and analyzing the genomes of a large number of well-characterized individuals in order to identify a broad range of AD risk and protective gene variants. The ultimate goal is to facilitate the identification of new pathways for therapeutic approaches and prevention. The analysis will also provide insight as to why individuals with known risk factor genes escape from developing AD.

The overarching goals of the ADSP are to: (1) identify new genomic variants contributing to increased risk of developing Late-Onset Alzheimer’s Disease (LOAD), (2) identify new genomic variants contributing to protection against developing Alzheimer’s Disease (AD) and Related Dementias (RD), (3) provide insight as to why individuals with known risk factor variants escape from developing AD, and (4) examine these factors to identify new genetically driven pathways leading to potential therapeutic approaches to disease prevention. (5) examine these factors in multi-ethnic populations. .Such a study of human genomic variation and its relationship to health and disease requires examination of a large number of study participants and needs to capture information about common and rare variants (both single nucleotide and copy number) together with high quality, rich phenotypes such as neuropathology, cognitive and neurological/neuropsychiatric assessments, imaging, and known and potential comorbidity and life-style risk factors. The ADSP conducts and facilitates analysis of sequence data to extend previous discoveries that may ultimately result in new directions for AD therapeutics. Data are being made available to the scientific community through the NIA Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS), a NIA-designated qualified access repository for AD and related dementia human genetics and genomics data. Investigators who are outside of the ADSP are encouraged to access and analyze these data.

From 2012 through 2017 the National Human Genome Research Institute (NHGRI) funded Large Scale Sequencing and Analysis Centers (LSACs): Baylor College of Medicine Human Genome Sequencing Center, the Broad Institute, the McDonnell Genome Institute at Washington University, and the New York Genome Center, participated in generating whole genome and whole exome sequence data for the first part of the study. In 2018, and Department of Defense-funded Uniformed Services University of the Health Sciences (USUHS), The American Genome Center (TAGC), began participating in the project.

The ADSP has moved through several phases during its early evolution. It includes several study approaches including case-control, epidiomology, and family based studies.

The ADSP Discovery Phase

The initial phase of the ADSP research plan is called the Discovery Phase. Samples were selected from well-characterized study cohorts of individuals with or without an AD diagnosis and the presence or absence of known risk factor genes. The ADSP generated three sets of genome sequence data for these samples as part of the Discovery Phase: (1) WGS for 584 samples from 113 multiplex families (two or more affected per family), (2) Whole Exome Sequence (WES) for 5,096 AD cases and 4,965 controls, and (3) WES of an Enriched sample set comprised of 853 AD cases from multiply affected families and 171 Hispanic controls. The Case-Control and Enriched Case Study spans 24 cohorts provided by the Alzheimer’s Disease Genetics Consortium (ADGC) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

As part of the Discovery Phase, the NIA ADSP genetics investigators funded under PAR-12-183 and the NHGRI funded Large Scale Sequencing and Analysis Centers (LSACs) conducted analysis of sequence data, including quality assessments and variant calling. Analysis of the Discovery Phase sequence data is anticipated to identify many new variations in the genome that may be implicated as new genetic risk or protective factors in older adults at risk for AD.

Because the initial analysis of WGS data in subjects from families multiply affected with AD revealed the occurrence of variations in the genome that were intergenic and intronic, in February of 2016 the external consultants to the ADSP recommended that further sequencing for the project should be of whole genomes.

The fully quality control checked (QC’d) data for the Discovery Phase study using Genome Reference Consortium Human Build 37 (GRCh37) was released in March of 2016 through the database of Genotypes and Phenotypes (dbGaP). Discovery Phase data called on Genome Reference Consortium Human Build 38 (GRCh38) are being shared through NIAGADS. Applicants for sequence data can obtain: (1) cleaned, quality control checked sequence data, (2) information on the composition of the study cohorts (e.g. case-control, family based, and epidemiology cohorts), (3) descriptions of the study cohorts included in the analysis, (4) accompanying phenotypic information such as age at disease onset, gender, diagnostic status, and cognitive measures, and (5) epidemiological information such as educational level and certain demographic data available on the subjects genotyped.

The ADSP Discovery Extension Phase

The ADSP Discovery Family-Based Extension Study:

To further assess the genomes in multiply affected families, under funding provided by NHGRI, an additional 427 samples were whole genome sequenced. This included 107 additional samples from families studied under the Discovery Phase, 175 samples from 47 new families, and 145 Hispanic Controls. This portion of the study is called the Discovery Extension Phase. The Family Based Study spans seven cohorts provided by the Alzheimer’s Disease Genetics Consortium (ADGC) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

The ADSP Discovery Case-Control Based Extension Study:

Under funding provided by NHGRI, an additional 3,000 subjects were whole genome sequenced. This included 1,466 cases and 1,534 controls. Of these 1,000 each of Non-Hispanic White (NHW), Caribbean Hispanic (CH), and African American (AA) descent were sequenced. Of these a total of 739 autopsy samples were sequenced [568 cases (500 NHW cases and 68 AA cases) and 171 controls (164 NHW and 7 AA)]. The Case-Control and Enriched Case Study spans 24 cohorts provided by the Alzheimer’s Disease Genetics Consortium (ADGC) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

The ADSP Follow-up Study (FUS)

The ADSP Discovery Phase identified a number of variations in the genomes of individuals affected with AD. These findings are being pursued in the ADSP Follow-Up Study (FUS), funded solely by NIA. The long-term goals of the ADSP FUS are to:

  • Move the field closer to enabling prediction of who will develop AD
  • Fully reveal the genetic architecture of AD in multiple ethnic groups
  • Better understand the underpinnings of AD pathogenesis
  • Aid the quest for therapeutic targets
  • Examine the AD genome in diverse populations

The ADSP Discovery Phase and the ADSP FUS are described under PAR-16-406. The ADSP FUS is leveraging existing infrastructure and collaborations to ensure continuity of ADSP participation. It provides funds for acquisition, archiving, sequencing, quality control, genome wide association studies (GWAS), and data sharing of the large number of samples from individuals affected by AD for WGS, as appropriate. Racial/ethnic diversity is an ongoing high NIA and ADSP priority. Well-phenotyped participants were selected with an emphasis on autopsy-confirmed and ethnically diverse cases/controls and availability of longitudinal data. Funds are being provided for both sequencing and data analysis. This effort is pursuing rare variants as comprehensively as possible, including consideration of statistical power, and exploration of a range of different populations containing those that are currently underrepresented in sequencing studies.

The majority of the samples from the ADSP Discovery and Discovery Extension phases were non-Hispanic white in origin, making the addition of ethnically diverse samples to the study critical to identification of both shared and novel genetic risk factors for AD among populations. Collection and sequencing of ethnically diverse cohorts is emphasized in the ADSP FUS, the goal being that additional existing cohorts with unrelated AD cases that encompass the richest possible ethnic diversity be given the highest priority for inclusion. For the United States this includes augmenting African American, Hispanic, and Asian cohorts.

Variants occur at different frequencies in different populations and certain risk variants may be much easier to detect in some populations. ADSP studies in ethnic groups including African American, Hispanic, and Asian remain statistically underpowered, so the genetics of these populations remain largely unstudied. Therefore, a major effort is being undertaken to augment the numbers of cases and controls in ethnically diverse populations in the United States. In order to understand the underlying substructure of the diversity populations, global studies are a key component of this effort.

To fulfill the goals of this ADSP FUS, cohorts of primary African Ancestry with a total of 8,863 participants; Hispanic/Latino and Amerindian Ancestry with 9,754 participants; Asian Ancestry with 7,000 participants and European Ancestry with 13,613 participants, were whole genome sequenced at The American Genome Center (TAGC) at the Uniformed Services University of the Health Sciences (USUHS) and the Center for Genome Technology John P. Hussman Institute for Human Genomics (HIHG CGT) in coordination with existing NIH-funded AD infrastructure including the National Cell Repository for Alzheimer’s Disease (NCRAD), NIAGADS, and the Genome Center for Alzheimer’s Disease (GCAD). Also included with the European Ancestry cohorts are Brain Autopsy participants with 1,058 Cases and 165 Controls that were sequenced. Cohort collection, phenotypic characterization, and whole genome sequencing were funded by the NIA.  This and additional information about the ADSP can be found on the National Institutes on Aging site.

The global effort brings important population sectors that were not previously well represented into the ADSP. Studies in the initial phase of the FUS have been supported by PAR-19-234 and PAR-17-214. The sequencing and analysis done under those FOAs have increased the numbers of participants and the volume of data. Data generated under this part of the ADSP will require novel methods to perform in-depth and subgroup analyses of diverse ethnic backgrounds, as well as integrated analyses to completely unravel the architecture of the AD genome. The ADSP FUS set the stage for the next wave of ADPS Studies called the ADSP Follow UP Study 2.0. The reach for this effort is global and includes Central and South America, Africa (9 countries), and Asia (India and Korea), and Australia, with additional efforts being planned.

The ADSP Follow-up Study (FUS) 2.0

The ADSP Follow-Up Study 2.0: The Diverse Population Initiative (PAR-21-212) was launched in 2021 to expand the sample set in ADSP to represent more diverse populations. The long-term goals of the ADSP FUS 2.0 are to:

  1. move the field closer to enabling prediction of who will develop AD;
  2. fully characterize AD subtypes by studying endophenotypes in diverse populations;
  3. better understand the differences in the genetic underpinnings of AD pathogenesis among diverse populations; and
  4. identify specific therapeutic targets based upon diverse population.

Numbers of Hispanic/Latino and Black/African American participants in the US remain insufficient to provide statistical significance for identification of rare or very rare variants. Variants in the Alzheimer’s genome are largely rare or very rare in the population. It is estimated that for 80% certainty for single variant testing for rare variants, ~16,100 cases and ~16,100 controls are needed for a variant with a minor allele frequency of 0.5% in the population; single variant testing for rare variants indicate that for 90% certainty, ~18,500 cases and ~18,500 controls are needed for each population for a variant with a minor allele frequency of 1% in the population. To ensure that there are sufficient numbers of study participants to achieve statistical power for analysis of rare or vary rare variants in the three largest diversity cohorts’ AD/ADRD genome given the available funding, the primary focus of the ADSP FUS 2.0 is on Hispanic/Latino, Black/African American, and Asian populations. Consortia are leveraging cohorts already recruited or in planning for recruitment to obtain sufficient numbers; sharing diversity data across consortia is essential to the success of this effort. Genetic samples and phenotypic data that are analyzed by the ADSP are provided by several consortia, initiatives, centers, and studies.

Some Additional ADSP Collaborations

New ADSP Initiatives

Functional Genomics Consortium. In July 2021, NIA awarded six U01 projects responding to the ADSP Functional Genomics Initiative RFA-AG-21-006. These awards comprise the core projects of the ADSP Functional Genomics Consortium. The Consortium will use a multipronged, team-science strategy and apply high-throughput, genome-wide approaches to discover and validate the functional roles and mechanisms of action of genes and variants underlying AD/ADRD.

ADSP Phenotype Harmonization Consortium (ADSP-PHC). The ADSP-PHC was formed in response to the NIA announcement of Harmonization of Alzheimer’s Disease and Related Dementias (AD/ADRD) Genetic, Epidemiologic, and Clinical Data to Enhance Therapeutic Target Discovery (PAR-20-099). The goal of the ADSP-PHC is to facilitate and perform phenotypic data harmonization for participants with ADSP genetic and genomic data which in turn requires bringing together experts in harmonization of relevant phenotypes. Endophenotypes to be harmonized include cognitive data, imaging, longitudinal clinical data, neuropathological data, cardiovascular risk data, and biomarkers. The harmonized phenotypic data will become a “legacy” dataset and will be perpetually curated and shared through a central data repository.

Machine Learning and Artificial Intelligence Consortium. In order to utilize the vast amount of data generated by the ADSP and other NIA funded initiatives, the NIA issued Cognitive Systems Analysis of Alzheimer’s Disease Genetic and Phenotypic Data (PAR-19-269) to apply cognitive systems approaches to the analysis of AD genetic and related data. Analysis of the data generated and harmonized by the ADSP will help to identify new genes and genetic pathways that will reveal risk and protective factors for AD and guide the field toward novel therapeutic approaches to the disease.

Detailed information about these three new NIA initiatives is located on the NIA website.

Last updated 04/13/22

  • Beecham, Gary
  • Bekris, Lynn M.
  • Bellen, Hugo J.
  • Boerwinkle, Eric
  • Botas, Juan
  • Bush, William S.
  • Byrd, Goldie
  • Chen, Feixiong
  • Chui, Helena
  • Cruchaga, Carlos
  • Cuccaro, Michael
  • Davatzikos, Christos
  • De Jager, Philip L.
  • Destefano, Anita L.
  • Dykxhoorn, Derek Michael
  • Farrer, Lindsay A.
  • Fornage, Myriam
  • Foroud, Tatiana
  • Goate, Alison
  • Haines, Jonathan L.
  • Harari, Oscar
  • Hohman, Timothy J.
  • Huang, Heng
  • Ji, Shuiwang
  • Jun, Gyungah
  • Kampmann, Martin
  • Karch, Celeste M.
  • Kardia, Sharon
  • Knowles, David
  • Kundaje, Anshul
  • Kunkle, Brian
  • Leal, Suzanne
  • Lee, Dong Young
  • Lee, Jinkook
  • Leverenz, James B.
  • Lichtarge, Olivier
  • Lin, Honguang
  • Martin, Eden R.
  • Mayeux, Richard P.
  • Miller, Gary W.
  • Milosavljevic, Aleksandar
  • Montgomery, Stephen B.
  • Montine, Thomas J.
  • Moore, Jason
  • Nho, Kwangsik Timothy
  • Pan, Wei
  • Park, Van My Ta
  • Pericak-Vance, Margaret
  • Piccio, Laura
  • Pumiglia, Kevin M.
  • Raj, Towfique
  • Reitz, Christiane
  • Ritchie, Marylyn
  • Salerno, William
  • Saykin, Andrew J.
  • Schellenberg, Gerard
  • Seshadri, Sudha
  • Shen, Li
  • Shulman, Joshua
  • St. George-Hyslop, Peter
  • Temple, Sally
  • Thompson, Paul M.
  • Toga, Arthur W.
  • Tosto, Giuseppe
  • Vance, Jeffrey
  • Vardarajan, Badri N.
  • Wang, Li-San
  • Wijsman, Ellen
  • Wolozin, Benjamin L.
  • Young, Juan Isaac
  • Zhang, Bin
  • Zhang, Xiaoling
  • Zhi, Degui
  • Zuloaga, Kristen L.
ADSP Discovery and Discovery + Extension Phase Sequencing and Analysis Grants

PAR-12-183 National Institute on Aging Analysis of Alzheimer’s Disease Genome Sequencing Project Data [U19]

  • Consortium for Alzheimer’s Sequence Analysis (CASA), UF1 AG047133; Gerard D. Schellenberg Project Period: June 15, 2014 – May 31, 2018
  • CHARGE: Identifying Risk & Protective SNV for AD in ADSP Case-control Sample, U01 AG049505; Sudha Seshadri
    Project Period: June 15, 2014 – May 31, 2018
  • Sequence-based Discovery of AD Risk & Protective Alleles, U01 AG049506; Eric A. Boerwinkle and William J. Salerno
    Project Period: June 15, 2014 – May 31, 2018
  • Sequence-based Discovery of AD Risk & Protective Alleles, U01 AG049507; Ellen M. Wijsman Project Period: June 15, 2014 – May 31, 2018

ADSP Replication and Extension

RFA-AG-16-002 Alzheimer’s Disease Sequencing Project (ADSP) Replication Phase Analysis Studies (U01)

  • Replication and Extension of ADSP Discoveries in African-Americans, U01 AG052410; Margaret A. Pericak-Vance, Gary W. Beecham, Goldie S. Byrd, and Richard P. Mayeux
    Project Period: June 15, 2016 – May 31, 2022
  • Identification and characterization of AD risk networks using multi-dimensional omics data, U01 AG052411; Alison M. Goate, Carlos Cruchaga, and Bin Zhang
    Project Period: July 15, 2016 – May 31, 2021
  • ADSP Follow-up in Multi-Ethnic Cohorts via Endophenotypes, Omics & Model Systems, U01 AG052409; Sudha Seshadri and Myriam Fornage
    Project Period: September 1, 2016 – May 31, 2021

PAR-15-356 Major Opportunities for Research in Epidemiology of Alzheimer’s Disease and Cognitive Resilience (R01)

  • Harmonized Diagnostic Assessment of Dementia (DAD) for Longitudinal Aging Study of India (LASI)-Genomic study, 5 U01 AG064948-03; Jinkook Lee and Sharon L. Kardia
    Project Period: September 15, 2019 – August 31, 2024
ADSP FOLLOW-UP STUDY: SEQUENCING AND ANALYSIS

PAR-16-406 Limited Competition: Additional Sequencing for the Alzheimer’s Disease Sequencing Project (U01)

  • Whole Genome Sequencing in Ethnically Diverse Cohorts for the ADSP Follow-Up Study (FUS), U01 AG057659; Margaret A. Pericak-Vance, Richard P. Mayeux, Badri N. Vardarajan
    Project Period: September 30, 2017 – August 31, 2022
  • Additional Sequencing Cohorts for the Alzheimer’s Disease Sequencing Project, U01 AG062943; Margaret A. Pericak-Vance and Richard P. Mayeux
    Project Period: September 1, 2019 – August 31, 2022

PAR-17-214 Limited Competition: Analysis of Data from NIA’s Alzheimer’s Disease Sequencing Project Follow-Up Study (U01)

  • The Familial Alzheimer Sequencing (FASe) Project, U01 AG058922; Carlos Cruchaga and Alison Goate
    Project Period: August 1, 2018 – July 31, 2023
  • Genomic approach to identification of microglial networks involved in Alzheimer disease risk, U01 AG058635; Alison M. Goate
    Project Period: August 1, 2018 – July 31, 2023
  • Therapeutic target discovery in ADSP data via comprehensive whole-genome analysis incorporating ethnic diversity and systems approaches, U01 AG058589; Anita L. DeStefano, Eric A. Boerwinkle, Phil L. De Jager, Myriam Fornage, Sudha Seshadri, and Ellen M. Wijsman
    Project Period: September 30, 2018 – August 31, 2023
  • The Alzheimer Disease Sequence Analysis Collaborative, U01 AG058654; Jonathan L. Haines, William S. Bush, Lindsay A. Farrer, Eden R. Martin, and Margaret A. Pericak-Vance
    Project Period: September 30, 2018 – August 31, 2023
  • Gene Discovery in Multi-ethnic Late-Onset Alzheimer’s Disease Families, U01 AG066752-02; Badri N. Vardarajan and Suzanne M. Leal
    Project Period: June 15, 2020 – May 31, 2025
  • KBASE2: Korean Brain Aging Study, Longitudinal Endophenotypes and Systems Biology, U01 AG072177; Andrew J. Saykin, Dong Young Lee, and Kwangsik Timothy Nho
    Project Period: April 1, 2021 – March 31, 2026

PAR-18-890 Limited Competition: Additional Sequencing for the Alzheimer’s Disease Sequencing Project: Opportunity for Revision Requests for Active Cooperative Agreements (U01)

  • Quality Control Activities for the ADSP Follow-Up Studies, U01 AG057659-03S1, Margaret A. Pericak-Vance, Richard P. Mayeux, and Badri Vardarajan
    Project Period: September 30, 2017 – August 31, 2022
  • Inclusion of sub-group of ASPREE samples into the ADSP, U01 AG066767-02S1, Jeffery Vance, Michael Cuccaro, and Brian Kunkle
    Project Period: September 30, 2021- June 30, 2025

PAR-19-234 Limited Competition: Additional Sequencing for the Alzheimer’s Disease Sequencing Project (U01)-competitive supplements to existing awards

  • Additional Sequencing for the Alzheimer’s Disease Sequencing Project (ADSP), U01 AG066767; Jeffery M. Vance, Michael L. Cuccaro, and Brian W. Kunkle
    Project Period: July 1, 2020 – June 30, 2025

PAR-14-070 Limited Competition: Renewal of, and Revisions to, the Alzheimer’s Disease Genetics Consortium (U01)

  • Alzheimer’s Disease Genetics Consortium, U01 AG032984; Gerard David Schellenberg
    Project Period, April 1, 2009 – March 31, 2025
ADSP FOLLOW-UP STUDY 2.0 DIVERSITY INITIATIVE: SEQUENCING AND ANALYSIS

PAR-21-212 Limited Competition: Alzheimer’s Disease Sequencing Project Follow-Up Study 2.0 (ADSP FUS 2.0): The Diverse Population Initiative (U01 Clinical Trial Not Allowed)

FUS 2.0 Diversity Initiative Recruitment and Retention of Diversity Cohorts

  • Asian Cohort for Alzheimers Disease (ACAD), R56 AG069130; Li-San Wang, Helena C. Chui, and Van My Ta Gyungah Park
    Project Period: September 30, 2020 – May 31, 2022

PAR-19-070 Research on Current Topics in Alzheimer’s Disease and Its Related Dementias (R01 Clinical Trial Optional)

  • Genetic Studies of Alzheimer Disease in Koreans, U01 AG062602; Lindsay Farrer
    Project Period: September 15, 2019 – August 31, 2024
ADSP INFRASTRUCTURE

PAR-16-047 National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (U24)

  • The NIA Genetics of Alzheimer’s Disease Data Storage Site, U24 AG041689; Li-San Wang
    Project Period: April 1, 2012 – March 31, 2022

RFA-AG-16-001 NIA Coordinating Center for Genetics and Genomics of Alzheimer’s Disease (U54)

  • Genome Center for Alzheimer’s Disease (GCAD), U54 AG052427; Gerard Schellenberg and Li-San Wang
    Project Period: April 15, 2016 – March 31, 2026

RFA-AG-22-001 National Institute on Aging (NIA) Late Onset of Alzheimer’s Disease (LOAD) Family- Based Study (FBS) (U24)

  • The National Institute on Aging (NIA) Late Onset of Alzheimer’s Disease (LOAD) Family-Based Study (FBS), U24 AG056270; Richard P. Mayeux, Tatiana M. Foroud, and Alison M. Goate
    Project Period: August 1, 2017 – May 31, 2022
PHENOTYPE HARMONIZATION

PAR-20-099 Harmonization of Alzheimer’s Disease and Related Dementias (AD/ADRD) Genetic, Epidemiologic, and Clinical Data to Enhance Therapeutic Target Discovery (U24 Clinical Trial Not Allowed)

  • Alzheimer’s Disease Sequencing Project Phenotype Harmonization Consortium, U24 AG074855; Timothy J. Hohman, Michael L. Cuccaro, and Arthur W. Toga
    Project Period: September 1, 2021 – August 31, 2026
ADSP FUNCTIONAL GENOMICS

RFA-AG-21-006 Alzheimer’s Disease Sequencing Project Functional Genomics Consortium (U01)

  • Alzheimer Variants: Propagation of Shared Functional Changes Across Cellular Networks, U01 AG072572; Philip L. De Jager and Peter St. George-Hyslop
    Project Period: July 15, 2021 – June 30, 2026
  • Circular RNAs and Their Interactions With RNA-Binding Proteins to Modulate AD-Related Neuropathology, 1 U01 AG072577; Xiaoling Zhang and Benjamin L. Wolozin
    Project Period: July 1, 2021 – June 30, 2026
  • Epidemiological Integration of Genetic Variants and Metabolomics Profiles in Washington Heights Columbia Aging Project, RF1 AG066107; Richard P. Mayeux, Gary W. Miller, and Badri Vardarajan
    Project Period: September 30, 2020 – August 31, 2024
  • Functional Genomic Dissection of Alzheimer’s Disease in Humans and Drosophila Models, U01 AG072439; Joshua M. Shulman, Hugo J. Bellen, Juan Botas, and Aleksandar Milosavljevic
    Project Period: July 1, 2021 – June 30, 2026
  • Functional Genomic Studies in Diverse Populations to Characterize Risk Loci for Alzheimer Disease, U01 AG072579; Jeffery M. Vance, Derek Michael Dykxhoorn, and Juan Isaac Young
    Project Period: July 15, 2021 – June 30, 2026
  • Genetic Epidemiology and Multi-Omics Analyses in Familial and Sporadic Alzheimer’s Disease among Secular Caribbean Hispanics and Religious Order, R01 AG067501; Richard P. Mayeux, Gary W. Miller, Tosto Giuseppe, and Badri Vardarajan
    Project Period: June 1, 2020 – March 31, 2025
  • Genetic Modifiers of Cerebrospinal Fluid TREM2 in Alzheimer’s Disease, RF1 AG058501; Carlos Cruchaga and Laura Piccio
    Project Period: July 15, 2018 – March 31, 2023
  • Identifying Protective Variants in Local Ancestry of African Americans for ApoE4, RF1 AG059018; Jeffery Vance
    Project Period: July 1, 2018 – March 31, 2023
  • Investigating the Functional Impact of AD Risk Genes on Neuro-Vascular Interactions, U01 AG072464; Sally Temple, Oscar Harari, Martin Kampmann, Celeste M. Karch, Kevin M. Pumiglia, and Kristen L. Zuloaga
    Project Period: July 1, 2021 – June 30, 2026
  • Mendelian Randomization for Unbias Biomarker Discovery for AD and Other Complex Traits, R01 AG057777; Oscar Harari
    Project Period: September 15, 2018 – May 31, 2023
  • Multi-Omic Functional Assessment of Novel AD Variants Using High-Throughput and Single-Cell Technologies, U01 AG072573; Thomas J. Montine, Anshul Kundaje, and Stephen B. Montgomery Project Period: July 1, 2021 – June 30, 2026
ADSP MACHINE LEARNING

PAR-19-269 Cognitive Systems Analysis of Alzheimer’s Disease Genetic and Phenotypic Data (U01)

  • Learning the Regulatory Code of Alzheimer’s Disease Genomes, 5 U01 AG068880-02; Towfique Raj and David A. Knowles
    Project Period: September 1, 2020 – August 31, 2025
  • Ultrascale Machine Learning to Empower Discovery in Alzheimer’s Disease Biobanks, 5 U01 AG068057; Paul M. Thompson, Christos Davatzikos, Heng Huang, Andrew J. Saykin, and Li Shen Project Period: September 15, 2020 – August 31, 2025
  • Alzheimer’s MultiOme Data Repurposing: Artificial Intelligence, Network Medicine, and Therapeutics Discovery, U01 AG073323; Feixiong Chen, Lynn M. Bekris, and James B. Leverenz Project Period: July 1, 2021 – June 30, 2026
  • Assessing Alzheimer Disease Risk and Heterogeneity Using Multimodal Machine Learning Approaches, U01 AG068221-01A1; Honguang Lin and Anita L. Destefano
    Project Period: July 1, 2021 – June 30, 2026
  • Cognitive Computing of Alzheimer’s Disease Genes and Risk, U01 AG068214; Olivier Lichtarge Project Period: July 1, 2021 – June 30, 2026
  • Genetics of Deep-Learning-Derived Neuroimaging Endophenotypes for Alzheimer’s Disease, U01 AG070112; Degui Zhi, Myriam Fornage, and Shuiwang Ji
    Project Period: July 1, 2021 – June 30, 2026
  • Artificial Intelligence Strategies for Alzheimers Disease Research; R01 AG066833; Jason Moore, Marylyn Ritchie, and Li Shen
    Project Period: September 30, 2021 – August 31, 2026
  • Causal and integrative deep learning for Alzheimers disease genetics; U01 AG073079; Wei Pan
    Project Period: September 15, 2021

Acknowledgment statement for any data distributed by NIAGADS:

Data for this study were prepared, archived, and distributed by the National Institute on Aging Alzheimer's Disease Data Storage Site (NIAGADS) at the University of Pennsylvania (U24-AG041689), funded by the National Institute on Aging.

For investigators using Alzheimer's Disease Sequencing Project data:

The Alzheimer’s Disease Sequencing Project (ADSP) is comprised of two Alzheimer’s Disease (AD) genetics consortia and three National Human Genome Research Institute (NHGRI) funded Large Scale Sequencing and Analysis Centers (LSAC). The two AD genetics consortia are the Alzheimer’s Disease Genetics Consortium (ADGC) funded by NIA (U01 AG032984), and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) funded by NIA (R01 AG033193), the National Heart, Lung, and Blood Institute (NHLBI), other National Institute of Health (NIH) institutes and other foreign governmental and non-governmental organizations. The Discovery Phase analysis of sequence data is supported through UF1AG047133 (to Drs. Schellenberg, Farrer, Pericak-Vance, Mayeux, and Haines); U01AG049505 to Dr. Seshadri; U01AG049506 to Dr. Boerwinkle; U01AG049507 to Dr. Wijsman; and U01AG049508 to Dr. Goate and the Discovery Extension Phase analysis is supported through U01AG052411 to Dr. Goate, U01AG052410 to Dr. Pericak-Vance and U01 AG052409 to Drs. Seshadri and Fornage.

Sequencing for the Follow Up Study (FUS) is supported through U01AG057659 (to Drs. PericakVance, Mayeux, and Vardarajan) and U01AG062943 (to Drs. Pericak-Vance and Mayeux). Data generation and harmonization in the Follow-up Phase is supported by U54AG052427 (to Drs. Schellenberg and Wang). The FUS Phase analysis of sequence data is supported through U01AG058589 (to Drs. Destefano, Boerwinkle, De Jager, Fornage, Seshadri, and Wijsman), U01AG058654 (to Drs. Haines, Bush, Farrer, Martin, and Pericak-Vance), U01AG058635 (to Dr. Goate), RF1AG058066 (to Drs. Haines, Pericak-Vance, and Scott), RF1AG057519 (to Drs. Farrer and Jun), R01AG048927 (to Dr. Farrer), and RF1AG054074 (to Drs. Pericak-Vance and Beecham).

The ADGC cohorts include: Adult Changes in Thought (ACT) (U01 AG006781, U19 AG066567), the Alzheimer’s Disease Research Centers (ADRC) (P30 AG062429, P30 AG066468, P30 AG062421, P30 AG066509, P30 AG066514, P30 AG066530, P30 AG066507, P30 AG066444, P30 AG066518, P30 AG066512, P30 AG066462, P30 AG072979, P30 AG072972, P30 AG072976, P30 AG072975, P30 AG072978, P30 AG072977, P30 AG066519, P30 AG062677, P30 AG079280, P30 AG062422, P30 AG066511, P30 AG072946, P30 AG062715, P30 AG072973, P30 AG066506, P30 AG066508, P30 AG066515, P30 AG072947, P30 AG072931, P30 AG066546, P20 AG068024, P20 AG068053, P20 AG068077, P20 AG068082, P30 AG072958, P30 AG072959), the Chicago Health and Aging Project (CHAP) (R01 AG11101, RC4 AG039085, K23 AG030944), Indiana Memory and Aging Study (IMAS) (R01 AG019771), Indianapolis Ibadan (R01 AG009956, P30 AG010133), the Memory and Aging Project (MAP) ( R01 AG17917), Mayo Clinic (MAYO) (R01 AG032990, U01 AG046139, R01 NS080820, RF1 AG051504, P50 AG016574), Mayo Parkinson’s Disease controls (NS039764, NS071674, 5RC2HG005605), University of Miami (R01 AG027944, R01 AG028786, R01 AG019085, IIRG09133827, A2011048), the Multi-Institutional Research in Alzheimer’s Genetic Epidemiology Study (MIRAGE) (R01 AG09029, R01 AG025259), the National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD) (U24 AG021886), the National Institute on Aging Late Onset Alzheimer’s Disease Family Study (NIA- LOAD) (U24 AG056270), the Religious Orders Study (ROS) (P30 AG10161, R01 AG15819), the Texas Alzheimer’s Research and Care Consortium (TARCC) (funded by the Darrell K Royal Texas Alzheimer’s Initiative), Vanderbilt University/Case Western Reserve University (VAN/CWRU) (R01 AG019757, R01 AG021547, R01 AG027944, R01 AG028786, P01 NS026630, and Alzheimer’s Association), the Washington Heights-Inwood Columbia Aging Project (WHICAP) (RF1 AG054023), the University of Washington Families (VA Research Merit Grant, NIA: P50AG005136, R01AG041797, NINDS: R01NS069719), the Columbia University Hispanic Estudio Familiar de Influencia Genetica de Alzheimer (EFIGA) (RF1 AG015473), the University of Toronto (UT) (funded by Wellcome Trust, Medical Research Council, Canadian Institutes of Health Research), and Genetic Differences (GD) (R01 AG007584). The CHARGE cohorts are supported in part by National Heart, Lung, and Blood Institute (NHLBI) infrastructure grant HL105756 (Psaty), RC2HL102419 (Boerwinkle) and the neurology working group is supported by the National Institute on Aging (NIA) R01 grant AG033193.

The CHARGE cohorts participating in the ADSP include the following: Austrian Stroke Prevention Study (ASPS), ASPS-Family study, and the Prospective Dementia Registry-Austria (ASPS/PRODEM-Aus), the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Erasmus Rucphen Family Study (ERF), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). ASPS is funded by the Austrian Science Fond (FWF) grant number P20545-P05 and P13180 and the Medical University of Graz. The ASPS-Fam is funded by the Austrian Science Fund (FWF) project I904), the EU Joint Programme – Neurodegenerative Disease Research (JPND) in frame of the BRIDGET project (Austria, Ministry of Science) and the Medical University of Graz and the Steiermärkische Krankenanstalten Gesellschaft. PRODEM-Austria is supported by the Austrian Research Promotion agency (FFG) (Project No. 827462) and by the Austrian National Bank (Anniversary Fund, project 15435. ARIC research is carried out as a collaborative study supported by NHLBI contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C). Neurocognitive data in ARIC is collected by U01 2U01HL096812, 2U01HL096814, 2U01HL096899, 2U01HL096902, 2U01HL096917 from the NIH (NHLBI, NINDS, NIA and NIDCD), and with previous brain MRI examinations funded by R01-HL70825 from the NHLBI. CHS research was supported by contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, and grants U01HL080295 and U01HL130114 from the NHLBI with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided by R01AG023629, R01AG15928, and R01AG20098 from the NIA. FHS research is supported by NHLBI contracts N01-HC-25195 and HHSN268201500001I. This study was also supported by additional grants from the NIA (R01s AG054076, AG049607 and AG033040 and NINDS (R01 NS017950). The ERF study as a part of EUROSPAN (European Special Populations Research Network) was supported by European Commission FP6 STRP grant number 018947 (LSHG-CT-2006-01947) and also received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013)/grant agreement HEALTH-F4- 2007-201413 by the European Commission under the programme “Quality of Life and Management of the Living Resources” of 5th Framework Programme (no. QLG2-CT-2002- 01254). High-throughput analysis of the ERF data was supported by a joint grant from the Netherlands Organization for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, the Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the municipality of Rotterdam. Genetic data sets are also supported by the Netherlands Organization of Scientific Research NWO Investments (175.010.2005.011, 911-03-012), the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), and the Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO) Netherlands Consortium for Healthy Aging (NCHA), project 050-060-810. All studies are grateful to their participants, faculty and staff. The content of these manuscripts is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the U.S. Department of Health and Human Services.

The FUS cohorts include: the Alzheimer’s Disease Research Centers (ADRC) (P30 AG062429, P30 AG066468, P30 AG062421, P30 AG066509, P30 AG066514, P30 AG066530, P30 AG066507, P30 AG066444, P30 AG066518, P30 AG066512, P30 AG066462, P30 AG072979, P30 AG072972, P30 AG072976, P30 AG072975, P30 AG072978, P30 AG072977, P30 AG066519, P30 AG062677, P30 AG079280, P30 AG062422, P30 AG066511, P30 AG072946, P30 AG062715, P30 AG072973, P30 AG066506, P30 AG066508, P30 AG066515, P30 AG072947, P30 AG072931, P30 AG066546, P20 AG068024, P20 AG068053, P20 AG068077, P20 AG068082, P30 AG072958, P30 AG072959), Alzheimer’s Disease Neuroimaging Initiative (ADNI) (U19AG024904), Amish Protective Variant Study (RF1AG058066), Cache County Study (R01AG11380, R01AG031272, R01AG21136, RF1AG054052), Case Western Reserve University Brain Bank (CWRUBB) (P50AG008012), Case Western Reserve University Rapid Decline (CWRURD) (RF1AG058267, NU38CK000480), CubanAmerican Alzheimer’s Disease Initiative (CuAADI) (3U01AG052410), Estudio Familiar de Influencia Genetica en Alzheimer (EFIGA) (5R37AG015473, RF1AG015473, R56AG051876), Genetic and Environmental Risk Factors for Alzheimer Disease Among African Americans Study (GenerAAtions) (2R01AG09029, R01AG025259, 2R01AG048927), Gwangju Alzheimer and Related Dementias Study (GARD) (U01AG062602), Hillblom Aging Network (2014-A-004-NET, R01AG032289, R01AG048234), Hussman Institute for Human Genomics Brain Bank (HIHGBB) (R01AG027944, Alzheimer’s Association “Identification of Rare Variants in Alzheimer Disease”), Ibadan Study of Aging (IBADAN) (5R01AG009956), Longevity Genes Project (LGP) and LonGenity (R01AG042188, R01AG044829, R01AG046949, R01AG057909, R01AG061155, P30AG038072), Mexican Health and Aging Study (MHAS) (R01AG018016), Multi-Institutional Research in Alzheimer’s Genetic Epidemiology (MIRAGE) (2R01AG09029, R01AG025259, 2R01AG048927), Northern Manhattan Study (NOMAS) (R01NS29993), Peru Alzheimer’s Disease Initiative (PeADI) (RF1AG054074), Puerto Rican 1066 (PR1066) (Wellcome Trust (GR066133/GR080002), European Research Council (340755)), Puerto Rican Alzheimer Disease Initiative (PRADI) (RF1AG054074), Reasons for Geographic and Racial Differences in Stroke (REGARDS) (U01NS041588), Research in African American Alzheimer Disease Initiative (REAAADI) (U01AG052410), the Religious Orders Study (ROS) (P30 AG10161, P30 AG72975, R01 AG15819, R01 AG42210), the RUSH Memory and Aging Project (MAP) (R01 AG017917, R01 AG42210Stanford Extreme Phenotypes in AD (R01AG060747), University of Miami Brain Endowment Bank (MBB), University of Miami/Case Western/North Carolina A&T African American (UM/CASE/NCAT) (U01AG052410, R01AG028786), Wisconsin Registry for Alzheimer’s Prevention (WRAP) (R01AG027161 and R01AG054047), Mexico-Southern California Autosomal Dominant Alzheimer's Disease Consortium (R01AG069013), Center for Cognitive Neuroscience and Aging (R01AG047649), and the A4 Study (R01AG063689, U19AG010483 and U24AG057437).

The four LSACs are: the Human Genome Sequencing Center at the Baylor College of Medicine (U54 HG003273), the Broad Institute Genome Center (U54HG003067), The American Genome Center at the Uniformed Services University of the Health Sciences (U01AG057659), and the Washington University Genome Institute (U54HG003079). Genotyping and sequencing for the ADSP FUS is also conducted at John P. Hussman Institute for Human Genomics (HIHG) Center for Genome Technology (CGT).

Biological samples and associated phenotypic data used in primary data analyses were stored at Study Investigators institutions, and at the National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD, U24AG021886) at Indiana University funded by NIA. Associated Phenotypic Data used in primary and secondary data analyses were provided by Study Investigators, the NIA funded Alzheimer’s Disease Centers (ADCs), and the National Alzheimer’s Coordinating Center (NACC, U24AG072122) and the National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS, U24AG041689) at the University of Pennsylvania, funded by NIA. Harmonized phenotypes were provided by the ADSP Phenotype Harmonization Consortium (ADSP-PHC), funded by NIA (U24 AG074855, U01 AG068057 and R01 AG059716) and Ultrascale Machine Learning to Empower Discovery in Alzheimer’s Disease Biobanks (AI4AD, U01 AG068057). This research was supported in part by the Intramural Research Program of the National Institutes of health, National Library of Medicine. Contributors to the Genetic Analysis Data included Study Investigators on projects that were individually funded by NIA, and other NIH institutes, and by private U.S. organizations, or foreign governmental or nongovernmental organizations.

The ADSP Phenotype Harmonization Consortium (ADSP-PHC) is funded by NIA (U24 AG074855, U01 AG068057 and R01 AG059716). The harmonized cohorts within the ADSP-PHC include: the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s study (A4 Study), a secondary prevention trial in preclinical Alzheimer's disease, aiming to slow cognitive decline associated with brain amyloid accumulation in clinically normal older individuals. The A4 Study is funded by a public-private-philanthropic partnership, including funding from the National Institutes of Health-National Institute on Aging, Eli Lilly and Company, Alzheimer's Association, Accelerating Medicines Partnership, GHR Foundation, an anonymous foundation and additional private donors, with in-kind support from Avid and Cogstate. The companion observational Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Study is funded by the Alzheimer's Association and GHR Foundation. The A4 and LEARN Studies are led by Dr. Reisa Sperling at Brigham and Women's Hospital, Harvard Medical School and Dr. Paul Aisen at the Alzheimer's Therapeutic Research Institute (ATRI), University of Southern California. The A4 and LEARN Studies are coordinated by ATRI at the University of Southern California, and the data are made available through the Laboratory for Neuro Imaging at the University of Southern California. The participants screening for the A4 Study provided permission to share their de-identified data in order to advance the quest to find a successful treatment for Alzheimer's disease. We would like to acknowledge the dedication of all the participants, the site personnel, and all of the partnership team members who continue to make the A4 and LEARN Studies possible. The complete A4 Study Team list is available on: a4study.org/a4-study-team.; the Adult Changes in Thought study (ACT), U01 AG006781, U19 AG066567; Alzheimer’s Disease Neuroimaging Initiative (ADNI): Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.;Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.;Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California; Estudio Familiar de Influencia Genetica en Alzheimer (EFIGA): 5R37AG015473, RF1AG015473, R56AG051876; Memory & Aging Project at Knight Alzheimer’s Disease Research Center (MAP at Knight ADRC): The Memory and Aging Project at the Knight-ADRC (Knight-ADRC). This work was supported by the National Institutes of Health (NIH) grants R01AG064614, R01AG044546, RF1AG053303, RF1AG058501, U01AG058922 and R01AG064877 to Carlos Cruchaga. The recruitment and clinical characterization of research participants at Washington University was supported by NIH grants P30AG066444, P01AG03991, and P01AG026276. Data collection and sharing for this project was supported by NIH grants RF1AG054080, P30AG066462, R01AG064614 and U01AG052410. We thank the contributors who collected samples used in this study, as well as patients and their families, whose help and participation made this work possible. This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/) and the Departments of Neurology and Psychiatry at Washington University School of Medicine; National Alzheimer’s Coordinating Center (NACC): The NACC database is funded by NIA/NIH Grant U24 AG072122. NACC data are contributed by the NIA-funded ADRCs: P30 AG062429 (PI James Brewer, MD, PhD), P30 AG066468 (PI Oscar Lopez, MD), P30 AG062421 (PI Bradley Hyman, MD, PhD), P30 AG066509 (PI Thomas Grabowski, MD), P30 AG066514 (PI Mary Sano, PhD), P30 AG066530 (PI Helena Chui, MD), P30 AG066507 (PI Marilyn Albert, PhD), P30 AG066444 (PI John Morris, MD), P30 AG066518 (PI Jeffrey Kaye, MD), P30 AG066512 (PI Thomas Wisniewski, MD), P30 AG066462 (PI Scott Small, MD), P30 AG072979 (PI David Wolk, MD), P30 AG072972 (PI Charles DeCarli, MD), P30 AG072976 (PI Andrew Saykin, PsyD), P30 AG072975 (PI David Bennett, MD), P30 AG072978 (PI Neil Kowall, MD), P30 AG072977 (PI Robert Vassar, PhD), P30 AG066519 (PI Frank LaFerla, PhD), P30 AG062677 (PI Ronald Petersen, MD, PhD), P30 AG079280 (PI Eric Reiman, MD), P30 AG062422 (PI Gil Rabinovici, MD), P30 AG066511 (PI Allan Levey, MD, PhD), P30 AG072946 (PI Linda Van Eldik, PhD), P30 AG062715 (PI Sanjay Asthana, MD, FRCP), P30 AG072973 (PI Russell Swerdlow, MD), P30 AG066506 (PI Todd Golde, MD, PhD), P30 AG066508 (PI Stephen Strittmatter, MD, PhD), P30 AG066515 (PI Victor Henderson, MD, MS), P30 AG072947 (PI Suzanne Craft, PhD), P30 AG072931 (PI Henry Paulson, MD, PhD), P30 AG066546 (PI Sudha Seshadri, MD), P20 AG068024 (PI Erik Roberson, MD, PhD), P20 AG068053 (PI Justin Miller, PhD), P20 AG068077 (PI Gary Rosenberg, MD), P20 AG068082 (PI Angela Jefferson, PhD), P30 AG072958 (PI Heather Whitson, MD), P30 AG072959 (PI James Leverenz, MD); National Institute on Aging Alzheimer’s Disease Family Based Study (NIA-AD FBS): U24 AG056270; Religious Orders Study (ROS): P30AG10161,R01AG15819, R01AG42210; Memory and Aging Project (MAP - Rush): R01AG017917, R01AG42210; Minority Aging Research Study (MARS): R01AG22018, R01AG42210; Washington Heights/Inwood Columbia Aging Project (WHICAP): RF1 AG054023;and Wisconsin Registry for Alzheimer’s Prevention (WRAP): R01AG027161 and R01AG054047. Additional acknowledgments include the National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS, U24AG041689) at the University of Pennsylvania, funded by NIA.

Last Updated 12.03.2024

  1. Nafikov RA. Analysis of pedigree data in populations with multiple ancestries: Strategies for dealing with admixture in Caribbean Hispanic families from the ADSP. Genet Epidemiol. 2018 Jun. doi: 10.1002/gepi.22133. PubMed link
  2. Naj AC. Quality control and integration of genotypes from two calling pipelines for whole genome sequence data in the Alzheimer’s disease sequencing project. Genomics. 2018 May. pii: S0888-7543(18)30281-7. PubMed link
  3. Raghavan S. Whole-exome sequencing in 20,197 persons for rare variants in Alzheimer’s disease. Annals of Clinical and Translational Neurology. 2018 Apr; 5(7): 832-842. bioRxiv link
  4. Butkiewicz M. Functional Annotation of genomic variants in studies of Late-Onset Alzheimer’s Disease. Bioinformatics. 2018 Mar; doi: 10.1093/bioinformatics/bty177. PubMed link
  5. Vardarajan BN. Whole genome sequencing of Caribbean Hispanic families with late-onset Alzheimer’s disease. Ann Clin Transl Neurol. 2018 Mar; 5(4): 406-417. PubMed link
  6. Blue EE. Genetic Variation in Genes Underlying Diverse Dementias May Explain a Small Proportion of Cases in the Alzheimer’s Disease Sequencing Project. Dement Geriatr Cogn Disord. 2018 Feb; 45(1-2): 1-17. PubMed link
  7. Crane PK. Alzheimer’s Disease Sequencing Project discovery and replication criteria for cases and controls: Data from a community-based prospective cohort study with autopsy follow-up. Science Direct. 2017 Dec; 13(10): 1410-43. PubMed link
  8. Beecham GW. The Alzheimer’s Disease Sequencing Project: Study design and sample selection. Neurol Genet. 2017 Oct; 3(5): e194. PubMed link
  9. Hollingworth P. Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer’s disease. Nat Genet. 2011 May; 43(5):429-35.
    PubMed link
  10. Naj AC. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer’s disease. Nat Genet. 2011 May; 43(5):436-41.
    PubMed link
  11. Seshadri S. Genome-wide analysis of genetic loci associated with Alzheimer disease. JAMA. 2010 May 12; 303(18):1832-40.
    PubMed link
  12. Harold D. Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer’s disease. Nat Genet. 2009 Oct; 41(10):1088-93.
    PubMed link
  13. Lambert JC. Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer’s disease. Nat Genet. 2009 Oct; 41(10):1094-9.
    PubMed link