Cross-platform proteomics signatures of extreme old age

2024  Journal Article

Cross-platform proteomics signatures of extreme old age

Pub TLDR

This research used two different platforms to analyze the serum proteome of individuals over 100 years old. They found 44 proteins associated with extreme old age, and 80 proteins that showed significant changes in expression related to pathways such as blood coagulation and IGF signaling.

DOI: 10.1101/2024.04.10.588876    PubMed ID: 38645061
 

College of Health researcher(s)

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Abstract

In previous work we used a Somalogic platform targeting approximately 5000 proteins to generate a serum protein signature of centenarians that we validated in independent studies that used the same technology. We set here to validate and possibly expand the results by profiling the serum proteome of a subset of individuals included in the original study using liquid chromatography tandem mass spectrometry (LC-MS/MS). Following pre-processing, the LC-MS/MS data provided quantification of 398 proteins, with only 266 proteins shared by both platforms. At 1% FDR statistical significance threshold, the analysis of LC-MS/MS data detected 44 proteins associated with extreme old age, including 23 of the original analysis. To identify proteins for which associations between expression and extreme-old age were conserved across platforms, we performed inter-study conservation testing of the 266 proteins quantified by both platforms using a method that accounts for the correlation between the results. From these tests, a total of 80 proteins reached 5% FDR statistical significance, and 26 of these proteins had concordant pattern of gene expression in whole blood. This signature of 80 proteins points to blood coagulation, IGF signaling, extracellular matrix (ECM) organization, and complement cascade as important pathways whose protein level changes provide evidence for age-related adjustments that distinguish centenarians from younger individuals.

Reed, E.R., Chandler, K.B., Lopez, P., Costello, C.E., Andersen, S., Perls, T.T., Li, M., Bae, H., Soerensen, M., Monti, S., Sebastiani, P.(2024)Cross-platform proteomics signatures of extreme old agebioRxiv