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Review Article

Proteomics and metabolomics in ageing research: from biomarkers to systems biology

Jessica M. Hoffman, Yang Lyu, Scott D. Pletcher, Daniel E.L. Promislow
Essays In Biochemistry Jul 11, 2017, 61(3) 379-388; DOI: 10.1042/EBC20160083
Jessica M. Hoffman
Department of Biology, University of Alabama at Birmingham, 1300 University Blvd CH464, Birmingham, AL 35294, U.S.A.
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Yang Lyu
Department of Molecular and Integrative Physiology and Geriatrics Center, Biomedical Sciences and Research Building, University of Michigan, Ann Arbor, MI 48109, U.S.A.
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Scott D. Pletcher
Department of Molecular and Integrative Physiology and Geriatrics Center, Biomedical Sciences and Research Building, University of Michigan, Ann Arbor, MI 48109, U.S.A.
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Daniel E.L. Promislow
Department of Pathology, University of Washington, Box 357705, 1959 NE Pacific Street, Seattle, Washington 98195, U.S.A.Department of Biology, University of Washington, Seattle, Washington 98195, U.S.A.
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  • For correspondence: promislo@uw.edu
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Abstract

Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible ‘biomarkers’, which are predictors of one’s biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying ‘endophenotypes’ in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity.

  • ageing
  • biological networks
  • metabolomics
  • proteomics
  • systems biology
  • Abbreviations

    AL,
    ad libitum;
    APOE,
    Apolipoprotein E;
    DR,
    dietary restricted;
    GWAS,
    genome-wide association studies;
    NF-kB,
    nuclear factor kappa-light-chain-enhancer of activated B cells;
    PPI,
    protein–protein interaction;
    T2D,
    Type 2 diabetes
    • © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society
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    July 2017

    Volume: 61 Issue: 3

    Essays In Biochemistry: 61 (3)
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    Proteomics and metabolomics in ageing research: from biomarkers to systems biology
    Jessica M. Hoffman, Yang Lyu, Scott D. Pletcher, Daniel E.L. Promislow
    Essays In Biochemistry Jul 2017, 61 (3) 379-388; DOI: 10.1042/EBC20160083
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    Proteomics and metabolomics in ageing research: from biomarkers to systems biology
    Jessica M. Hoffman, Yang Lyu, Scott D. Pletcher, Daniel E.L. Promislow
    Essays In Biochemistry Jul 2017, 61 (3) 379-388; DOI: 10.1042/EBC20160083

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    • Article
      • Abstract
      • Introduction
      • Proteomics and metabolomics as ageing biomarkers
      • Metabolic pathways associated with ageing
      • Cellular network stability and ageing
      • Integrating multiple ‘omics’ into ageing research
      • Conclusions
      • Summary
      • Competing Interests
      • Funding
      • Author Contribution
      • Acknowledgments
      • References
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    Keywords

    Ageing
    biological networks
    metabolomics
    proteomics
    systems biology

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