PREPARE Challenge: Data for Early Prediction (Phase 1)

Find, curate, or contribute data to help the National Institute of Aging, a center of the National Institute of Health, create representative and open datasets that can be used for the early prediction of Alzheimer's disease and related dementias. #health

$200,000 in prizes
jan 2024
376 joined


Alzheimer's disease and Alzheimer's disease related dementias (AD/ADRD) are a set of brain disorders affecting more than 6 million Americans. The main clinical features of AD/ADRD are progressive impairments of cognition and function and changes in behavior. Alzheimer’s is currently ranked as the seventh leading cause of death in the United States and is the most common cause of dementia among older adults.

Although AD is the most frequently diagnosed form of dementia, ADRDs exhibit similar cognitive and pathological characteristics, making them challenging to differentiate from AD. In fact, many patients clinically diagnosed with Alzheimer's have different mixtures of brain pathologies, complicating both diagnosis and treatment. ADRDs include Frontotemporal degeneration (FTD), Lewy body dementia (LBD), Vascular contributions to cognitive impairment and dementia (VCID), Mixed-Etiology dementias (MED).

Early intervention may be important for successful disease modification. For example, promising advances in pharmacotherapy treatments that slow the progression of dementia would benefit from earlier detection. However, early prediction of cognitive decline and AD/ADRD is significantly limited, including diagnosis at presymptomatic or early stages of disease. Standard research and clinical tools are not currently not sensitive enough to predict AD/ADRD onset earlier.

Potentially more sensitive approaches (e.g. neuroimaging, fluid biomarkers, neuropsychological tasks, and digital and passive measures) can be expensive, difficult to interpret, or have unclear performance in some individuals and groups, and may require access to academic medical centers, protected databases, or industry partners to ascertain data. Data sources, analytical algorithms, interpretations, and applications of test results have known (and unknown) biases, methodological limitations, and questionable predictive validity, especially in groups that have historically been underrepresented in or excluded from participation in AD/ADRD research.

Opportunities and disparities in prediction and diagnosis

The NIA seeks to stimulate the use of data resources with appropriate sample diversity, including data relevant to communities disproportionately burdened by AD/ADRD.

For example, for Asian, Black, or Hispanic older adults, the amount of the protein amyloid—which has long been considered a biological hallmark for AD—might have a smaller role in determining cognitive impairment than other factors such as co-occurring chronic medical conditions (hypertension, diabetes) and sociodemographic and systemic factors, each of which has been found to contribute to racial and ethnic disparities in dementia diagnoses (Wilkins et al., 2022; Dark and Walker, 2022).

This highlights the importance of identifying novel biomarkers, including non-biological (e.g., social determinants of health) predictors in adults from underrepresented racial and ethnic groups. The goal of this challenge competition is to inform novel approaches to early detection that might ultimately lead to more accurate tests, tools, and methodologies for clinical and research purposes.

A graphic of a pixelated brain on the left and an illustrated brain on the right.

Image by Gerd Altmann from Pixabay

Data sources

Artificial intelligence, machine learning, and computing offer opportunities for intelligent data collection and analysis to understand AD-related changes. To address the need for data from a wider set of sources and types, including data relevant to low-resourced, underserved communities disproportionately burdened by AD/ADRD, the aim of the challenge is to find, access, and use data from sources such as:

These are only examples and data need not be limited to sources generated by NIH-supported research. By leveraging these resources and exploring novel approaches, we hope to develop more accurate tests and methodologies for early detection of AD/ADRD.

The National Institute of Aging (NIA)

The National Institute of Aging (NIA), one of the 27 Institutes and Centers of the National Institute of Health (NIH), leads a broad scientific effort to understand the nature of aging and to extend the healthy, active years of life. NIA is the primary Federal agency supporting and conducting Alzheimer's disease research.

Eureka Prize Competitions

This challenge is a Eureka Prize Competition, and is aligned with the objectives of the 42 U.S.C. 283q, which calls on NIH to support challenges in areas of biomedical science that could: 1) realize significant advancements and 2) improve health outcomes in human diseases and conditions, particularly with respect to human diseases and conditions for which public and private investment in research is disproportionately small relative to Federal Government expenditures on prevention and treatment activities, that are serious and represent a significant disease burden in the United States, or for which there is potential for significant return on investment to the United States.

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