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Active NON-SBIR/STTR RPGS NIH (US)

Precision Aging Network: Closing the Gap Between Cognitive Healthspan andHuman Lifespan

$117.68M USD

Funder NATIONAL INSTITUTE ON AGING
Recipient Organization University of Arizona
Country United States
Start Date Sep 30, 2021
End Date Aug 31, 2026
Duration 1,796 days
Number of Grantees 1
Roles Principal Investigator
Data Source NIH (US)
Grant ID 10491806
Grant Description

SUMMARY/ABSTRACT: Overall Project The strategic vision of the Precision Aging Network (PAN) is to develop the essential scientific knowledge to understand the discrepancy that currently exists between cognitive healthspan and human lifespan. We must reveal the neural mechanisms that 1) account for optimal brain performance in old age resulting in healthy

cognitive function, and 2) those that underlie decline in brain function leading to age-related cognitive impairment (ARCI), Alzheimer’s disease (AD), or Alzheimer’s disease-related dementias (ADRD). The ultimate goal of the PAN is to develop not only a strong scientific foundation for the essential knowledge needed to

match cognitive healthspan with human lifespan, but also to leverage big data approaches that apply precision medicine concepts to prolong optimal brain function. To achieve this goal of sustaining optimal cognitive function in old age, and to extend quality of life for people across levels of risk for ARCI, AD, or ADRD,

we maintain that methodologies such as those developed and implemented in the PAN will be required. Although ‘chronological age’ is consistently associated with increasing incidence of disability, including chronic brain disorders such as AD and ADRD, the exact mechanistic relationships between ‘biological age’ and

decline in brain function is not known. The number of people now living with some form of dementia is estimated to be 50 million worldwide, which is expected to double every 20-years. Because of the enormous heterogeneity in brain and cognitive function among individuals in their 70s, 80s and 90s, the urgent challenge

for science, medicine and healthcare providers is to discover interventions that are individually effective in delaying or preventing ARCI, AD, or ADRD. Untangling the complex relationship between age and cognitive performance requires a strategy that includes the study of very large, diverse, well-characterized and longitudinally sampled populations. This will require

‘big data’ but also the means to translate the massive amounts of information gathered into ‘smart data’ or ‘knowledge’. This demands radically different conceptual models. Currently, no single approach adequately identifies the means to modify personal aging trajectories for improved brain health in individuals. The

approach proposed in PAN is designed to overcome obstacles of earlier methods. The focus is on how to distinguish the various combinations of age, sex, genetics, race-ethnicity, health, lifestyle choices and environmental factors that influence brain drivers that increase susceptibility to dysfunction, as well as

those factors that increase brain protection and resistance against dysfunction. The fundamental principle of the precision medicine approach is to ’individualize’. This will enable strong and specific predictions for each person to close the gap between cognitive healthspan and human lifespan. The root of this concept is in the teachings of Hippocrates, who said – “It is more important to know

what sort of person has a disease than to know what sort of disease a person has.”

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University of Arizona

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