There is a fundamental gap in our knowledge of healthy aging: while we understand how to genetically alter the average lifespan of many organisms, we do not understand why some individuals within every population lead longer and/or healthier lives (or shorter / less healthy lives) than this average. This is critical knowledge: under- standing why some humans live longer or shorter than expected for their genotype could lead to diagnostics to identify those at risk for short life or ill health, or even interventions to induce these long-lived, healthy states. This work will use genetically identical C. elegans to study inter-individual variability in aging. Though this variability is often disregarded as ?biological noise?, our overarching hypothesis is that inter-individual differences in lifespan and healthspan result from regulated processes that can be understood, predicted, and altered. To study this, we developed an innovative imaging system in which many isolated C. elegans are reared in identical environments, permitting lifelong measurement of reporter expression and physiological function. The specific objective of this proposal is to identify the genetic basis of two sets of intriguing observations we made using this system. First, we found that transcriptional regulation of the microRNAs mir-71 and lin-4 causes young adults to commit to a particular future lifespan.
Aim 1 will genetically dissect this process of fate com- mitment. Second, we found that the traditional measure of healthspan, the population average, is confounded because it can be improved in two distinct ways: (1) by increasing the maximum possible healthspan, or (2) by increasing the proportion of individuals within the population that attain this maximum.
Aim 2 will identify the ge- netic pathways by which each of these two aspects of healthspan can be altered. The hypothesis of Aim 1 is that, early in adulthood, a ?lifespan commitment network? of transcriptional regu- lators drives mir-71 and lin-4 to different, stable set-points in different individuals. We have two potent assays for the activity of the network, and we know that different set-points lead to different lifespans via the insulin/ IGF-1-like signaling pathway (IIS). We propose to use classic techniques in genetic analysis to identify the last remaining unknown: the upstream regulators surrounding mir-71 and lin-4 that constitute this network.
Aim 2 will test the hypothesis that IIS mutants influence each of the two aspects of healthspan, which our tools now allow us to directly measure, through distinct mechanisms. Specifically, we propose: (1) that IIS influences maximal healthspan via the same effector pathways by which it increases lifespan; but (2) that IIS influences the fraction of the population reaching that maximum by lifespan-independent effects on pathogen resistance. This work is innovative, both in the techniques used to study individual animals and to score healthspan, and in the specific hypotheses to be tested. It will have significant impact by identifying genetic interactions that allow specific individuals within a population to enjoy extended lifespan and health. These interactions will represent natural targets for future interventions.

Public Health Relevance

Why do some individuals live longer than others, or lead healthier or less-healthy lives? In addition to genetic and environmental differences, we propose that early in life, certain genes act differently in long- vs. short-lived in a way that determines their future fates. We will identify these genes, define the relationship between long life and good health, and determine how that relationship can be altered to selectively extend the span of healthy living.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
1R01AG057748-01A1
Application #
9662175
Study Section
Cellular Mechanisms in Aging and Development Study Section (CMAD)
Program Officer
Guo, Max
Project Start
2019-02-01
Project End
2023-11-30
Budget Start
2019-02-01
Budget End
2019-11-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Washington University
Department
Genetics
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130