Longevity Consortium

We study human exceptional longevity and healthy aging and we have generated many results that connect genetic variants to these traits, to intermediate molecular profiles, including gene expression, serum proteomics and metabolomics, and to nutrition. We would like to use the genetic, methylation and phenotypic data generated in the
HRS
for replication of our results linking genetics, multiomics profiles of cognitive aging, and nutrition.
We will use these data to investigate the associations between genetic variants, multi-omics profiles, longevity and healthy cognitive aging, and nutrition using mixed effect models adjusted by genome-wide principal components and including random effects with variance covariance matrix that depends on the genetic relation matrix. We will investigate the relations between genetic variants and multi-omics profile using our pipeline for yQTL that uses mixed effect models as above. We will integrate the various results using mediation analysis.
We will ask for access to deidentified data and not biological specimens.

Our research focuses on understanding why some people live longer and age more healthily, especially when it comes to brain function and nutrition. The study has found many links between genes and these healthy aging traits by looking at different biological factors like gene activity and blood proteins. We aim to leverage the HRS data to confirm our findings. We will analyze this information to explore how genes, biological markers, and nutrition work together to influence long life and healthy brain aging. The data used will be anonymous, ensuring privacy, and no physical samples will be needed.