In Vivo Large-Scale Mapping of Protein Turnover in Human Cerebrospinal Fluid

The extraction of accurate physiological parameters from
clinical
samples provides a unique perspective to understand disease etiology
and evolution, including under therapy. We introduce a new methodologic
framework to map patient proteome dynamics in vivo, either proteome-wide
or in large targeted panels. We applied it to ventricular cerebrospinal
fluid (CSF) and could determine the turnover parameters of almost
200 proteins, whereas a handful were known previously. We covered
a large number of neuron biology- and immune system-related proteins,
including many biomarkers and drug targets. This first large data
set unraveled a significant relationship between turnover and protein
origin that relates to our ability to investigate organ physiology
with protein-labeling strategy specifics. Our data constitute the
first draft of CSF proteome dynamics as well as a repertoire of peptides
for the community to design new analyses. The disclosed methods apply
to other fluids or tissues provided sequential sample collection can
be performed. We show that the proposed mathematical modeling applies
to other analytical methods in the field.