Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pcbi.1007162
Title: Cross-species functional modules link proteostasis to human normal aging
Authors: Komljenovic, Andrea
Li, Hao
Sorrentino, Vincenzo 
Kutalik, Zoltan
Auwerx, Johan
Robinson-Rechavi, Marc
Keywords: Science & Technology
Life Sciences & Biomedicine
Biochemical Research Methods
Mathematical & Computational Biology
Biochemistry & Molecular Biology
GENE-EXPRESSION PROFILES
LIFE-SPAN
DIETARY RESTRICTION
COMMON SIGNATURES
AGE
METAANALYSIS
INTEGRATION
MECHANISMS
EXTENSION
LONGEVITY
Issue Date: 3-Jul-2019
Publisher: PUBLIC LIBRARY SCIENCE
Citation: Komljenovic, Andrea, Li, Hao, Sorrentino, Vincenzo, Kutalik, Zoltan, Auwerx, Johan, Robinson-Rechavi, Marc (2019-07-03). Cross-species functional modules link proteostasis to human normal aging. PLOS COMPUTATIONAL BIOLOGY 15 (7). ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pcbi.1007162
Abstract: The evolutionarily conserved nature of the few well-known anti-aging interventions that affect lifespan, such as caloric restriction, suggests that aging-related research in model organisms is directly relevant to human aging. Since human lifespan is a complex trait, a systems-level approach will contribute to a more comprehensive understanding of the underlying aging landscape. Here, we integrate evolutionary and functional information of normal aging across human and model organisms at three levels: gene-level, process-level, and network-level. We identify evolutionarily conserved modules of normal aging across diverse taxa, and notably show proteostasis to be conserved in normal aging. Additionally, we find that mechanisms related to protein quality control network are enriched for genes harboring genetic variants associated with 22 age-related human traits and associated to caloric restriction. These results demonstrate that a systems-level approach, combined with evolutionary conservation, allows the detection of candidate aging genes and pathways relevant to human normal aging.
Source Title: PLOS COMPUTATIONAL BIOLOGY
URI: https://scholarbank.nus.edu.sg/handle/10635/247797
ISSN: 1553-734X
1553-7358
DOI: 10.1371/journal.pcbi.1007162
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