Towards a Signature of Age in Blood Plasma

Various tools are presently under development as means to measure age from tissue samples, such as by looking at DNA methylation patterns. A marker for biological age is very much needed in order to speed up development of treatments for aging, as it is presently very expensive and time-consuming to evaluate any sort of putative longevity-enhancing therapy. This is true even in rodents, where it can cost millions of dollars and take three to five years to run a single life span study - and the costs only grow for longer-lived mammals. If much of that could be replaced by a short test carried out immediately before and after treatment then research could proceed much more rapidly. Here is one example of work that might lead to such a marker for age:

Metabolomic and glycomics analysis of blood samples have successfully been used to identify key molecular mechanisms underlying human health and aging. Additional molecular signatures of health and aging can be found using high-throughput proteomics. However, due to the high cost, this has been relatively understudied. Recently, three studies on aging using high-throughput proteomics identified proteins whose plasma levels and cerebrospinal fluid (CSF) levels substantially change with increasing age. However, these studies either did not apply a correction for multiple testing or did not validate their findings in independent cohorts. Proteomics profiling in the CSF study was obtained using SOMAscan, a Slow Off-rate Modified Aptamer (SOMAmer)-based capture array. SOMAscan involves the use of SOMAmers (single-stranded DNA aptamers) to assay proteins in multiplex using DNA microarrays. As such, SOMAscan quantifies the level of the subproteome of proteins targeted by SOMAmers. A total of 1,129 of these SOMAmers are currently available.

The SOMAscan approach has previously been used by us and others to study plasma proteins related to Alzheimer and related phenotypes. In this study, we use the SOMAscan approach to assess the extent to which proteins are correlated with chronological age in a cohort of female twins with independent replication. We further investigate gene expression levels for those proteins that correlate with age using RNAseq data from whole blood in twins. Finally, we examine the association of specific proteins with factors relating to biologic aging such as birthweight and cardiovascular risk.

Eleven proteins were associated with chronological age and were replicated at protein level in an independent population. These were further investigated at gene expression level in 384 females from the TwinsUK cohort. The two most strongly associated proteins were chordin-like protein 1 and pleiotrophin. Chordin-like protein 1 was also significantly correlated with birthweight and with the individual Framingham 10-years cardiovascular risk scores in TwinsUK. Pleiotrophin is a secreted growth factor with a plethora of functions in multiple tissues and known to be a marker for cardiovascular risk and osteoporosis. Our study highlights the importance of proteomics to identify some molecular mechanisms involved in human health and aging.

Link: http://biomedgerontology.oxfordjournals.org/content/early/2014/08/13/gerona.glu121.long