This Funding Opportunity Announcement (FOA) invites applications specific to sample acquisition, genome wide association studies, whole genome sequencing, quality control checking, variant calling, data calling, data sharing, data harmonization, and analysis that will support the generation of data from multi-ethnic cohorts for the Alzheimer's Disease Sequencing Project Follow-Up Study 2.0: The Diverse Population Initiative.Funding Opportunity Description
Background

This Funding Opportunity Announcement (FOA) is issued in response to National Alzheimer's Project Act (NAPA) milestones for the genetics of Alzheimer's disease (AD) and AD-related dementias (ADRD) in order to support the ongoing Alzheimer's Disease Sequencing Project (ADSP). The overarching goals of the ADSP are to: 1) identify new genes involved in AD/ADRD; 2) identify gene alleles contributing to increased risk for, or protection against, the disease; 3) provide insight as to why individuals with known risk factor genes escape from developing AD/ADRD; 4) identify potential avenues for therapeutic approaches and prevention of the disease; and 5) fully reveal the genetic architecture of AD/ADRD in multiple race and ethnicity categories. The samples for the ADSP were selected from well-characterized, diverse study cohorts of individuals both with and without an AD diagnosis as well as with and without known risk-factor genes. This study of human genetic variation and its relationship to health and disease involves a large number of study participants and aims to capture not only common single nucleotide variations, but also rare copy number and other structural variants that are increasingly thought to play an important role in complex diseases.

This FOA uses the Office of Management and Budget (OMB) official categories of race and ethnicity. For the purposes of this FOA, ethnic categories (i.e., Hispanic/Latino) and racial categories (i.e., American Indian/Alaska Native; Asian; and Black/African American) will be referred to as diverse populations . Cohorts of participants from individual ethnic or race categories will be referred to as diversity cohorts . Individuals in diversity cohorts will be referred to as diversity participants .

The ADSP has identified a large number of variations in the genomes of individuals affected with AD. The study population for these analyses was predominantly White. Lack of diversity in the sample set limits the possible clinical utility of emerging tools and methodological approaches for identifying potential therapeutics for a large proportion of the population. This, in turn, underscores the urgency to ensure appropriate representation of diverse populations to prevent potential gaps in the translation of research efforts to these populations. To this end, the initial ADSP findings will be pursued in diverse populations in the next phase of the study, called the ADSP Follow-Up Study (FUS) 2.0: The Diverse Population Initiative and referred to here as ADSP FUS 2.0. 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.

Important instances of unique AD/ADRD genetic variation have already been identified in epidemiological cohorts with Hispanic/Latino and Black/African American participants. Variants for AD are rare and can only be identified with a larger number of study participants. Variants occur at different frequencies in different populations, and certain risk variants may be much easier to detect in some populations. US diversity groups are not represented in ADSP data in sufficient numbers to enable meaningful study, so the genetics of these populations remain largely unstudied. Hispanics/Latinos, Blacks/African Americans, and Asians are the largest and fastest-growing minority groups in the US, and AD/ADRD imposes a high economic and social burden upon the US population. US Asian population ADSP genetic data are completely absent.

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 will be on Hispanic/Latino, Black/African American, and Asian populations. Consortia should take advantage of 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. Investigators with cohorts representing other racial/ethnic categories, such as American Indians/Alaskan Natives, are encouraged to apply for funding separately under other NIA-supported FOAs. Sequencing of participants from founder populations such as those from Africa and Asia is allowed under this FOA in order to understand population substructure and ancestry-informative markers. A small amount of sequencing of Whites to bring significance to the 90% certainty of significance level will be allowed for rare or very rare variants for the US population; however, it is expected that the vast majority of sequencing in the ADSP FUS 2.0 will be done in Hispanics/Latinos, Blacks/African Americans, and Asians.

Accelerated identification of AD/ADRD genes, gene clusters, and endophenotypes driven by genetic and ethnic/racial characteristics will move the field toward selection of participants with similar endophenotypes to improve outcomes of clinical trials. The community is now able to layer different types of data to identify these endophenotypes. Analytic approaches are being developed for analysis of structural and rare variants, endophenotypes, and cross-phenotype genetic analyses to modify and/or apply analytic methods to data that are increasingly complex. In order to identify optimal drug targets, the full landscape of genetic variants must be identified and characterized.

Much work remains to develop analytic methods and resources to understand the functional significance of variants, particularly noncoding variants, in diverse populations. Under this funding opportunity announcement, studies that perform analysis of sequence data may include analysis of the functional genomic studies of regions of interest. Diversity datasets will need to be integrated and harmonized to fully annotate the AD genome. This may mean assembling annotation data such as that provided by ENCODE and similar approaches to help understand whether clusters of genes in the same network or with common function may be a component of the disease etiology that varies by ethnic and racial category. Applicants are encouraged to devise analysis plans to include data from genome wide association studies (GWAS) for AD; imputation analysis; ADSP whole exome and exome chip data, and whole genome AD sequencing efforts; related genetic data such as in deep (long read) sequencing analyses generated on AD subjects; and functional genomics data.

Research Objectives

NIA intends to support studies most likely to meet a major goal of this FOA: to identify and confirm a full set of rare variants contributing to AD/ADRD endophenotypes in diversity cohorts to enhance the probability of identifying potential therapeutic approaches for risk and prevention. Both sequencing and data analysis will be supported under this FOA. Applicants to this FOA for the ADSP FUS 2.0 should propose to: 1) sequence particular diverse study cohorts; 2) analyze either the entire dataset (cases and controls) or components of the dataset; or 3) both sequence and analyze these data. Justification for the choice of the approach must be provided. Applicants proposing to analyze only a component of the total cohort (i.e., selected cohorts or diverse subpopulations) should propose power calculations that support the likelihood of gene discovery. Applicants should design plans that clearly define which ADSP FUS 2.0 datasets, diverse subpopulations, and/or endophenotypes will be analyzed. Along with analysis of data funded under the present FOA, analysis plans for the ADSP FUS 2.0 should include data from diversity cohorts in the ADSP FUS funded under PAR-17-214, PAR-18-890, and PAR-19-234 where possible. The design and use of large-scale storage capacity with appropriate security and backup measures to support analytical capabilities should be considered.

Successful applications are anticipated to involve research conducted by multidisciplinary teams of investigators and should describe a comprehensive plan to develop leading-edge, innovative approaches for the analysis of whole genome sequence (WGS) and related genetic data. Analysis should encompass the criteria set out by the ADSP FUS funded under PAR-17-214, "Analysis of Data from NIA's Alzheimer's Disease Sequencing Project Follow-Up Study (U01)." In particular, these criteria include ethnic/racial diversity; autopsy-confirmed cases/controls, especially for non-European ancestry; availability of longitudinal data; no age limit for cases; cases unrelated to each other; and availability of comparable controls.

It is expected that the scientific environment in which the work will be done will contribute to the probability of success of the project and of the ADSP as a whole. Institutional support, equipment and other physical resources available to the investigators should be adequate for the project proposed, leveraging existing NIA-funded resources. Both the project itself and the ADSP should benefit from unique features of the scientific environment, subject populations, or collaborative arrangements. For applicants performing data analysis, it is expected that they will have the capacity to analyze whole-genome sequence data from sufficient numbers of affected and unaffected individuals to achieve statistical significance for rare or very rare variants in diverse groups.

The successful milestone-driven ADSP FUS 2.0 application would consist of a group of researchers with expertise in the genetics of complex neurological diseases, including AD, and the field of whole genome sequencing, as well as statisticians and other experts who will participate in study design and analysis. Successful applicant(s) may be expected to collaborate not only within their own study, but also with other PD(s)/PI(s) funded under this and related FOAs. Engagement of existing NIA-supported infrastructure is considered essential to the success of the project, so applicants should plan to financially support the National Central Cell Repository for Alzheimer’s Disease (NCRAD); The American Genome Center (TAGC) at the Uniformed Services University for the Health Sciences (USUHS) or another NIA-approved, large-scale sequencing center; the Genome Center for Alzheimer's Disease (GCAD); and the NIA Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS) for their efforts in the ADSP.

Applicants should develop key quantitative milestones with a timeline for accomplishment. Quality control (QC) and data harmonization will be performed by GCAD. The order and process for data transfer, quality control checking, and data harmonization will be agreed upon by the ADSP as a whole and will follow closely the existing paradigm.

Under the present FOA, the ADSP will improve the likelihood of analyzing sequence data on enough different examples of events that change the genetic architecture of AD such that these data, when analyzed with existing ADSP datasets, will enhance the ability to better understand the genetic underpinnings of AD and to obtain a better understanding of rare risk and protective variants. The availability of high-quality, extensive phenotypic information on study participants is a critical consideration. Study design should include analysis of data from study participants with quantitative trait measures to more clearly define endophenotypes. Similarly, participants whose data will be used as controls should be well characterized.

Applications considered for funding must effectively leverage NIA and NIH investments in infrastructure to support studies related to the genetics of Alzheimer’s disease. The investigators funded under this FOA may utilize information from existing NIA- and NIH-funded research resources or other federal websites such as:

The NIA Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS)
The Genome Center for Alzheimer's Disease (GCAD)
The National Central Cell Repository for Alzheimer’s Disease (NCRAD)
The National Alzheimer's Coordinating Center (NACC)
The Alzheimer's Disease Genetics Consortium (ADGC)
The Alzheimer's Disease Research Centers (ADRCs)
Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)
The Collaborative for Alzheimer’s Disease Research (CADRE)
The Alzheimer's Disease Neuroimaging Initiative (ADNI)
Alzheimer's Disease Related Dementias (ADRD)
The National Alzheimer’s Project Act (NAPA)
Other websites designed to store and distribute data related to AD