January 6, 2022
PAR-22-093, Research on Current Topics in Alzheimer's Disease and Its Related Dementias (R01 Clinical Trial Optional)
PAR-22-094, Research on Current Topics in Alzheimer's Disease and Its Related Dementias (R21 Clinical Trial Not Allowed)
National Institute on Aging (NIA)
Note that applications proposing exploratory or developmental projects for which there are insufficient preliminary data as well as certain focused secondary analysis projects should consider applying to PAR-22-094 (R21), whereas projects that already have sufficient preliminary data or a very strong and well-developed scientific premise should apply to PAR-22-093 (R01).
The etiology of Alzheimer’s disease (AD) and its related dementias (ADRD) is complex. Our existing cohort studies of both AD/ADRD and cognitive aging include social, behavioral, environmental, cognitive, neuroimaging, biomarker, genetic, epigenetic, and other measures assessed longitudinally and collected initially ever earlier in the lifespan. Indeed, it is becoming clear that both risk and protective factors include exposures and experiences in early and mid-life, long before the appearance of any neuropathology or notable cognitive decline. Continued progress in the epidemiology of both AD/ADRD and cognitive resilience is therefore likely to require more diverse and representative cohorts, more participants, more variables, and more occasions of measurement. Additionally, greater collaboration among diverse scientific disciplines will be needed. Moreover, applicants should consider sex as a biological variable.
This Notice of Special Interest (NOSI) encourages investigator-initiated research on all aspects of cognitive epidemiology relevant to AD/ADRD and cognitive resilience, but identifies specific areas that build on current efforts supported by NIA as well as gaps and opportunities identified in the 2018 and 2021 Alzheimer’s Disease Research Summits. The following areas are of particular interest to the NIA:
Augmenting existing longitudinal cohort studies
The National Institutes of Health (NIH) supports a broad range of population-based studies to address questions related to the trajectory of Alzheimer’s disease and other aging phenotypes. The collection and analysis of new phenotypic information, including, but not limited to, enhanced measures of cognition and function, new biomarkers, neuroimaging, and digital data on physiology, cognition, behavior, function, and exposures from wearable sensors, could broaden the impact of existing studies. The addition of genetic data to existing or newly collected cohorts in the light of existing or novel phenotypes would allow analyses of how specific genetic variants or polygenic risk scores contribute to the risk of, or protection against, AD/ADRD and the trajectory of cognitive performance. Other emerging opportunities stem from the wider availability of electronic health records and administrative data (e.g., CMS Medicare claims), contextual measures capturing information about the social, policy, and physical environment, and the ability to collect phenotypic data online at lower cost.
Guidance for purchasing Identifiable Centers for Medicare and Medicaid Services (CMS) data in NIA grant applications can be found in NOT-AG-21-055.
Enabling precision medicine for AD/ADRD through deep phenotyping
The precision-medicine approach presents new opportunities for understanding the behavioral, social, environmental, and molecular determinants of AD/ADRD risk and cognitive resilience in diverse populations and at the level of the individual. This NOSI invites applications that will enhance the potential of community-based cohort studies to enable precision medicine for AD/ADRD by, for example: expanding the types of cross-sectional and longitudinal ante- and post-mortem-biospecimen data collection needed to generate multiple layers of “omics” data; incorporating dense molecular endophenotyping (e.g., genomic, epigenomic, proteomic, metabolomic, and microbiomic); collecting nontraditional data modalities using wearable sensors and mobile-health technologies (sometimes referred to as digital phenotyping); and embedding biomarkers of environmental exposure and geocodes. The large-scale multidimensional data generated with the above approaches could serve as the basis for future systems biology and gene-environment studies as well as the development of a new taxonomy for AD/ADRD prevention.
Enhancing the power of multiethnic cohort studies.
The multi-factorial etiology and heterogeneity of AD/ADRD may reveal itself in racial or ethnic differences in overall AD/ADRD risk and in putative risk or protective factors or in the progression of neuropathology and cognitive decline. Although multi-ethnic cohorts can be very informative, well-powered cohort studies are needed to identify specific risk or protective factors that vary between (sub)populations. These cohorts may also benefit from the addition of measures that may help us better identify the determinants of both disease risk and cognitive resilience, including behavioral and social factors, that often pattern with race/ethnicity, such as education. The 2018 and 2021 Alzheimer’s Disease Research Summits include a recommendation to establish new cohorts and/or expand existing cohorts for intense endophenotyping that are sufficiently powered to analyze the effects of gender and diverse populations.
Exploring of trends in the risk of AD/ADRD and their explanation via putative risk and protective factors.
Recent research in well-characterized cohorts suggests the age-specific risk of AD/ADRD may be declining in some populations and increasing in others. The answer to the trend question has clear implications for public health and policy. Trend data also provide a potentially powerful way to test whether putative risk or protective factors are truly causal. For example, educational attainment appears to be protective against AD/ADRD, whereas both cardiovascular disease (CVD) and female sex may confer additional risk. But the reasons for these observed patterns are not yet clear. The risk posed by female sex status, for example, may reflect sex differences affecting the disease process, which may include differences in the trajectory of hormonal changes with age or in the sex chromosome, or difference in behavioral and social risk or protective factors that pattern with gender such as educational attainment or all of these. Comparisons between cohorts differing in these factors over time will be informative and may require sophisticated analyses or meta-analyses and replication plans.
Collecting and sequencing DNA samples from well-characterized cases and controls.
Research conducted by investigators from the Alzheimer’s Disease Sequencing Project (ADSP) and others has demonstrated the value of whole-genome and whole-exome sequencing in the detection of genetic variants that may modify AD risk or protection. The sequencing of more genomes of well-characterized cases and controls as well as family-based cohorts from large multiply-affected families will accelerate gene discovery for target identification efforts and accelerate the progress of the drug development pipeline. Well-characterized subjects from diversity sample sets are especially needed to augment statistical power. Applicants interested in this line of research should be aware of current and emerging NIH guidance with respect to sharing genomic data and are expected to facilitate rapid data-sharing according to existing ADSP and NIA policies, which include providing all types of data to the ADSP NIAGADS/dbGaP database.
Electronic archiving of cohort studies and linkage to administrative data
Although NIH encourages broad and inclusive data-sharing for large studies, electronic archiving of data from many longitudinal cohorts is either incomplete or relies on data infrastructure that is vulnerable to research-funding lapses. The current NIH Strategic Plan for Data Science focuses on enhancing the discoverability and usability of data sets, developing appropriate analysis tools, and providing special opportunities for collaboration between epidemiologists and survey scientists on the one hand, and computer and data scientists on the other. In addition to a wealth of information relevant to cognitive epidemiology that is trapped in non-digitized or obsolete formats, there are other highly relevant data sets and biospecimen collections that have never been publicly shared, as well as surveys where the greater availability of paradata and metadata would benefit researchers. We welcome all applications that will make more data available for use by the research community as expeditiously as possible, and likewise encourage dissemination efforts that enhance the discoverability of these data.
Harmonizing complex data sets relevant to AD/ADRD
Although there have been substantial efforts at NIH to develop brief, reliable measures (e.g., PROMIS® and the NIH Toolbox®) as well as recommendations for the use of off-the-shelf phenotypic measures (e.g., PhenX) in large epidemiological studies, there has been less work on creating crosswalks between these measures and those that have been historically used in cohort studies. The need for harmonization across these platforms is particularly acute in studies that include longitudinal clinical, neuroimaging, genetic and genomic, and biomarker data that are costly to obtain. Coordination and harmonization of data from existing cohort studies with the Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Accelerating Medicines Partnership (AMP) effort for AD/ADRD, datasets available in the Gateway to Global Aging Data, and the ADSP are also welcome.
Harmonizing dementia assessment, additional data collection, and analysis to enhance cross-national comparisons.
As important as harmonization is to the study of dementia trends and the risk and protective factors (against dementia) that differ between cohorts, more work is needed on the harmonization of dementia-assessment methods that could inform cross-national comparisons. This requires more than simple translation of instruments, since even the best ones may not operate equivalently in low- and middle-income countries (LMICs) where literacy rates and levels of educational attainment are much lower. Two recent examples where this work is being done are the 10/66 Dementia Research Group in lower income countries and more recent work done within the US-based Health and Retirement Study (HRS). Both examples use a Harmonized Cognitive Assessment Protocol (HCAP) that can be used to compare dementia prevalence in higher- and lower-income countries.
Applications to use or extend these approaches, or develop new approaches to harmonize dementia assessments suitable for cross-national comparisons and feasible both in clinical and field settings, are encouraged, including harmonization of HCAP data and/or developing crosswalks between HCAP and non-HCAP data. Evaluations of the quality of HCAP and non-HCAP data related to the assessment of dementia are also encouraged. In addition, applications proposing the collection of data in LMIC using the HRS/HCAP framework are encouraged, as well as analysis of international HRS/HCAP data to identify risk and protective factors for dementia and illuminate causal mechanisms.
Application and Submission Information
This notice applies to due dates on or after March 11, 2022 and subsequent receipt dates through November 13, 2024.
Submit applications for this initiative using one of the following funding opportunity announcements (FOAs) or any reissues of these announcement through the expiration date of this notice.
All instructions in the SF424 (R&R) Application Guide and the funding opportunity announcement used for submission must be followed, with the following additions:
For funding consideration, applicants must include “NOT-AG-21-045” (without quotation marks) in the Agency Routing Identifier field (box 4B) of the SF424 R&R form. Applications without this information in box 4B will not be considered for this initiative.
Applications nonresponsive to terms of this NOSI will not be considered for the NOSI initiative.