TY - JOUR
T1 - Proteomics and metabolomics in ageing research
T2 - From biomarkers to systems biology
AU - Hoffman, Jessica M.
AU - Lyu, Yang
AU - Pletcher, Scott D.
AU - Promislow, Daniel E.L.
N1 - Funding Information:
We would like to thank the two reviewers for their insightful comments on the manuscript. This work was supported by the Glenn/AFAR Postdoctoral Fellowship; National Institutes of Health (NIH) [grant numbers AG049494 (to D.P.), AG030593, AG051649 (to S.P.), GM102279 (to S.P., D.P. and Y.L.), CA211160 (to D.P.)]; and National Science Foundation [grant number DMS1561814 (to D.P.)].
Publisher Copyright:
© 2017 The Author(s).
PY - 2017/7/11
Y1 - 2017/7/11
N2 - Age is the single greatest risk factor for a wide range of diseases, and as themean 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 powerfulmodel needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity.
AB - Age is the single greatest risk factor for a wide range of diseases, and as themean 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 powerfulmodel needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity.
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U2 - 10.1042/EBC20160083
DO - 10.1042/EBC20160083
M3 - Review article
C2 - 28698311
AN - SCOPUS:85023609617
SN - 0071-1365
VL - 61
SP - 379
EP - 388
JO - Essays in Biochemistry
JF - Essays in Biochemistry
IS - 3
ER -
