title: Systems biology and longevity: an emerging approach to identify innovative anti-aging targets and strategies.
abstract: Human aging and longevity are complex and multi-factorial traits that result from a combination of environmental, genetic, epigenetic and stochastic factors, each contributing to the overall phenotype. The multi-factorial process of aging acts at different levels of complexity, from molecule to cell, from organ to organ systems and finally to organism, giving rise to the dynamic "aging mosaic". At present, an increasing amount of experimental data on genetics, genomics, proteomics and other -omics are available thanks to new high-throughput technologies but a comprehensive model for the study of human aging and longevity is still lacking. Systems biology represents a strategy to integrate and quantify the existing knowledge from different sources into predictive models, to be later tested and then implemented with new experimental data for validation and refinement in a recursive process. The ultimate goal is to compact the new acquired knowledge into a single picture, ideally able to characterize the phenotype at systemic/organism level. In this review we will briefly discuss the aging phenotype in a systems biology perspective, showing four specific examples at different levels of complexity, from a systemic process (inflammation) to a cascade-process pathways (coagulation) and from cellular organelle (proteasome) to single gene-network (PON-1), which could also represent targets for anti-aging strategies.
authors.affiliation: CIG - Interdepartmental Centre L Galvani, University of Bologna, Bologna, Italy.
authors.forename: E
authors.initials: E
authors.lastname: Cevenini
authors.forename: E
authors.initials: E
authors.lastname: Bellavista
authors.forename: P
authors.initials: P
authors.lastname: Tieri
authors.forename: G
authors.initials: G
authors.lastname: Castellani
authors.forename: F
authors.initials: F
authors.lastname: Lescai
authors.forename: M
authors.initials: M
authors.lastname: Francesconi
authors.forename: M
authors.initials: M
authors.lastname: Mishto
authors.forename: A
authors.initials: A
authors.lastname: Santoro
authors.forename: S
authors.initials: S
authors.lastname: Valensin
authors.forename: S
authors.initials: S
authors.lastname: Salvioli
authors.forename: M
authors.initials: M
authors.lastname: Capri
authors.forename: A
authors.initials: A
authors.lastname: Zaikin
authors.forename: D
authors.initials: D
authors.lastname: Monti
authors.forename: J P
authors.initials: JP
authors.lastname: de Magalhães
authors.forename: C
authors.initials: C
authors.lastname: Franceschi
mesh_terms: D000367:Age Factors; D000375:Aging / Q000502:physiology*; D015195:Drug Design; D006801:Humans; D008136:Longevity / Q000502:physiology*; D008954:Models, Biological; D049490:Systems Biology