Notice to Specify High-Priority Research Topic for PAR-19-070 and PAR-19-071

Notice Number: NOT-AG-18-053

Key Dates
Release Date: December 17, 2018

Related Announcements

NOT-AG-22-007 - Notice to Expire NOSIs to PAR-19-070, "Research on Current Topics in Alzheimer's Disease and Its Related Dementias (R01 Clinical Trial Optional)"

NOT-AG-22-006 - Notice to Expire NOSIs to PAR-19-070, "Research on Current Topics in Alzheimer's Disease and Its Related Dementias (R01 Clinical Trial Optional)"


Issued by
National Institute on Aging (NIA)


This Notice of Information specifies a high-priority topic of interest for PAR-19-070 "Research on Current Topics in Alzheimer's Disease and Its Related Dementias (R01 Clinical Trial Optional)" and PAR-19-071 Research on Current Topics in Alzheimer's Disease and Its Related Dementias (R21 Clinical Trial Not Allowed) .

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 using the R21 FOA, whereas projects that already have sufficient preliminary data or a very strong and well-developed scientific premise should use the R01 FOA.

Major Opportunities for Research in Epidemiology of Alzheimer's Disease and Related Dementias and Cognitive Resilience


The etiology of Alzheimer’s disease and related dementias (AD/ADRD) has proven to be more complex than expected. Our existing cohort studies of both AD/ADRD and cognitive aging include social, behavioral, 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 cohorts, more diverse cohorts, more participants, more variables, and more occasions of measurement. Additionally, greater collaboration among diverse scientific disciplines will be needed.

Research Objectives

This high-priority topic 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 and new recommendations from the 2018 Alzheimer’s Disease Research Summit (see: for more information). 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 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 new biomarkers, neuroimaging, and non-traditional data modalities such as that 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) and the ability to collect phenotypic data online at lower cost.

Enabling precision medicine for AD/ADRD through deep molecular phenotyping

The precision-medicine approach (see: presents new opportunities for understanding the molecular determinants of AD/ADRD risk and cognitive resilience in diverse populations and at the level of the individual. This Notice 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; 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 and 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. 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 better help us identify the determinants of both disease risk and cognitive resilience. The 2015 Alzheimer’s Disease Research Summit includes a recommendation to establish new 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 gender differences in 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; see: 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 and family based cohorts from large multiply-affected families will accelerate gene discovery for target identification efforts and to 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 (see: 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

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 (see: for additional information) focuses on enhancing the discoverability and usability of data sets and developing appropriate analysis tools, 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 ; see: for more information) 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; see: for more), the Accelerating Medicines Partnership (AMP) effort for AD/ADRD (see:, and the ADSP (see: are also welcome.

Harmonizing dementia assessment 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 developing countries 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 (see: in lower income countries and more recent work done within the US-based Health and Retirement Study (HRS; see: 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 assessment suitable for cross-national comparisons and feasible both in clinical and field settings are encouraged.


Please direct all inquiries to:

Dallas W. Anderson, Ph.D.
Division of Neuroscience
National Institute on Aging (NIA)
Telephone: 301-496-1494

Jonathan W. King, Ph.D.
Division of Behavioral and Social Research
National Institute on Aging (NIA)
Telephone: 301-402-4156