About Exceptional Longevity

Hosting the EL research resources alongside Alzheimer’s Disease resources on the AD Knowledge Portal will enhance opportunities for data mining and integrative analyses across various data types. This approach aims to identify omics profiles linked to EL and to explore factors that may contribute to protection against age-related dementias and Alzheimer’s Disease.

What is Exceptional Longevity?

Exceptional longevity (EL) is an extreme phenotype characterized by the ability to maintain a long and healthy life. The factors that contribute to achieving exceptional health span are likely to vary across different physiological systems (such as respiratory, cardiovascular, and immune systems) and functional areas (including mobility and cognition). By understanding how protective human genetic variants and cellular factors influence exceptional survival, we may identify new targets for interventions that can replicate their beneficial effects.

NIA-supported projects that focus on exceptionally long-lived individuals are exploring the genetic and molecular factors linked to lower morbidity, reduced mortality, and increased survival into older ages. These projects are generating extensive data on genetics, multi-omics, and phenotypic characteristics. Additionally, they are integrating information from various species with different life spans, which may help identify molecular factors and tissue-specific pathways that influence human health and longevity. By contextualizing findings from model organisms within human cohorts, researchers aim to uncover conserved biological pathways that could enhance health and lifespan across different species.

The NIA-supported EL projects consist of several initiatives:

• the Long-Life Family Study (LLFS)

• the Longevity Consortium (LC)

• the Longevity Genomics (LG)

• the Integrative Longevity Omics (ILO) projects.

These projects have produced a wealth of complex, multi-dimensional biological data and various research resources. These resources include data and biospecimens from long-lived individuals, cross-species comparisons, analytical tools, drug screening databases, and advanced algorithms. In the coming years, these projects are expected to generate large volumes of omics data, such as transcriptomics, methylomics, proteomics, and metabolomics.