Philipp Geyer (Presenter)
Max Planck Institute of Biochemistry
Authorship: Philipp E. Geyer1,2*, Nicolai J. Wewer Albrechtsen2,3,4*, Stefka Tyanova1, Niklas Grassl1, Eva W. Iepsen3,4, Julie Lundgren3,4, Sten Madsbad4,5, Jens J. Holst3,4, Signe S. Torekov3,4, Matthias Mann1,2†
1Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany 2NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark 3Department of Biomedical Sciences, Faculty of Health and Medical Sciences, Univer
| Short Abstract We have developed an automated and robust shotgun proteomics workflow for the streamlined MS-analysis of single drops of blood (´Plasma Proteome Profiling´, Geyer et al. Cell Systems 2016). Here we applied this approach to 1294 separate plasma proteomes to assess dynamic effects due to weight loss. Among the wide-ranging effects of weight loss (93 significantly affected proteins) were individual specific changes in apolipoprotein profiles. Correlation analysis of plasma proteins to patient data defined a panel of ten inflammation proteins and revealed individual specific-longitudinal inflammation profiles. Participants with high or low level inflammation profiles gained from weight loss. |
Long Abstract
The blood plasma proteome is a unique reflection of an individual´s physiology, as it integrates genetic background and environmental factors. Mass spectrometry (MS)-based proteomics should be an ideal technology to discover and quantify proteins in this clinically accessible and relevant body fluid. However, the enormous dynamic range of protein abundances and the complex sample composition make MS-based plasma proteomics extremely challenging. Generally, workflows for plasma proteomics have been extremely laborious and involve the depletion of high abundant plasma proteins by antibodies, which can lead to compromised quantitation. We previously combined advances in liquid chromatography, mass spectrometry, and computational analysis to develop an automated, rapid and robust shot gun proteomics workflow that allowed the streamlined analysis of hundreds of plasma proteins from a single drop of blood, a technology that we call ´plasma proteome profiling´ (1). Here we applied this new approach to a first clinical study in which we measured 1294 plasma proteomes to assess dynamic effects on the plasma proteome due to weight loss
Weight loss and sustained weight maintenance is of central concern in modern society, research and especially medicine. Obesity and the metabolic syndrome are major public health burden, predisposing to several diseases including type 2 diabetes and cardiovascular diseases and increasing the overall likelihood of early death. However, the effects on an individual´s health state remain ill-defined and it is not known how the proteome itself reacts to weight changes.
We investigated a longitudinal cohort of 52 severely obese study participants by measuring their plasma proteomes over an initial weight loss period of 8 weeks, followed by a one year weight maintenance period. Most of the individual-specific protein levels remained constant over time whereas several groups of functionally connected proteins like apolipoproteins showed correlated regulation over time. Weight loss itself had a broad effect on the human plasma proteome with 93 significantly changed proteins. The adipocyte secreted SERPINF1 and the apolipoprotein APOF1 were most significantly down and up regulated with fold-changes of -16% and +37%, respectively (p<10-13). Correlation analysis of the plasma proteins to several standard clinical parameters such as the body mass index, allowed us to define a panel consisting of ten inflammation proteins, which yielded a longitudinal, individual-specific inflammation profile. Nearly all of the study participants benefited from weight loss regarding their inflammation profile and the few individuals that did not benefit generally showed some weight regain. Moreover, this inflammation profile separated the cohort in participants with high and low inflammation levels. Interestingly both groups showed a similar benefit from weight loss.
Comprehensive quantitation of the apolipoprotein family – the main lipid turnover mediators – delivered unprecedented information on metabolic and cardiovascular risk factors that were influenced by weight loss. Our overall conclusion is that weight loss has a beneficial effect on the metabolic profile as well as systematic low-grade inflammation in severely obese subjects.
References & Acknowledgements:
1) Geyer PE, Kulak NA, Pichler G, Holdt LM, Teupser D, Mann M. Plasma Proteome Profiling to Assess Human Health and Disease. Cell Syst 2, 185-195 (2016).
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