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Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine
Published on: January 26, 2024
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Personal aging markers and ageotypes revealed by deep longitudinal profiling.
Sara Ahadi1, Wenyu Zhou1, Sophia Miryam Schüssler-Fiorenza Rose1
1Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Nature Medicine
|January 15, 2020
Summary
This study reveals distinct molecular aging patterns, or
Area of Science:
- Gerontology
- Molecular Biology
- Systems Biology
Background:
- The molecular mechanisms underlying human aging remain incompletely understood.
- Comprehensive profiling is needed to identify age-related molecular changes.
Purpose of the Study:
- To investigate age-related molecular alterations using multiomics data.
- To identify distinct aging patterns ('ageotypes') in individuals.
Main Methods:
- Longitudinal multiomics profiling (transcripts, proteins, metabolites, cytokines, microbes) in 106 healthy adults (29-75 years).
- Correlation analysis of molecular data with chronological age.
- Identification of individual aging patterns based on molecular pathway changes.
Main Results:
- Identified known and novel age-associated molecular markers.
- Discovered distinct aging profiles in insulin-resistant versus insulin-sensitive individuals.
- Defined personalized aging patterns ('ageotypes') based on longitudinal molecular changes.
Conclusions:
- 'Ageotypes' offer a molecular snapshot of individual aging, influenced by lifestyle and health.
- This approach may aid in monitoring and intervening in the aging process.
- Multiomics profiling provides deep insights into the heterogeneity of human aging.
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