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Protein signatures from blood plasma and urine suggest changes in vascular function and IL-12 signaling in elderly with a history of chronic diseases compared with an age-matched healthy cohort

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Abstract

Key processes characterizing human aging are immunosenescence and inflammaging. The capacity of the immune system to adequately respond to external perturbations (e.g., pathogens, injuries, and biochemical irritants) and to repair somatic mutations that may cause cancers or cellular senescence declines. An important goal remains to identify genetic or biochemical, predictive biomarkers for healthy aging. We recruited two cohorts in the age range 70 to 82, one afflicted by chronic illnesses (non-healthy aging, NHA) and the other in good health (healthy aging, HA). NHA criteria included major cardiovascular, neurodegenerative, and chronic pulmonary diseases, diabetes, and cancers. Quantitative analysis of forty proinflammatory cytokines in blood plasma and more than 500 proteins in urine was performed to identify candidate biomarkers for and biological pathway implications of healthy aging. Nine cytokines revealed lower quantities in blood plasma for the NHA compared with the HA groups (fold change > 1.5; p value < 0.025) including IL-12p40 and IL-12p70. We note that, sampling at two timepoints, intra-individual cytokine abundance patterns clustered in 86% of all 60 cases, indicative of person-specific, highly controlled multi-cytokine signatures in blood plasma. Twenty-three urinary proteins were differentially abundant (HA versus NHA; fold change > 1.5; p value < 0.01). Among the proteins increased in abundance in the HA cohort were glycoprotein MUC18, ephrin type-B receptor 4, matrix remodeling–associated protein 8, angiopoietin-related protein 2, K-cadherin, and plasma protease C1 inhibitor. These proteins have been linked to the extracellular matrix, cell adhesion, and vascular remodeling and repair processes. In silico network analysis identified the regulation of coagulation, antimicrobial humoral immune responses, and the IL-12 signaling pathway as enriched GO terms. To validate links of these preliminary biomarkers and IL-12 signaling with healthy aging, clinical studies using larger cohorts and functional characterization of the genes/proteins in cellular models of aging need to be conducted.

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Data availability

All detailed datasets (medical data, quantitative cytokine and urinary proteome surveys) and methods used for analysis are included in the “Materials and methods” section and in the Supplemental Files. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD012477 (reviewer account details: username: reviewer44087@ebi.ac.uk; password: qAT4NwUo).

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Acknowledgments

We thank Mr. Zachary Gortler for contributions to human subject recruitment and specimen collections, and Ms. Lauren DiLello for medical data collection and discussions on biomarker analysis strategies.

Funding

This work was generously funded by the Ruggles Family Foundation, Moline, IL and Mr. and Mrs. Rudy Ruggles.

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Author notes

  1. Yanbao Yu and Harinder Singh contributed equally to this work.

Authors and Affiliations

  1. J. Craig Venter Institute, 9605 Medical Center Drive, Rockville, MD, 20850, USA

    Yanbao Yu, Harinder Singh, Keehwan Kwon, Tamara Tsitrin, Karen E. Nelson & Rembert Pieper

  2. J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA, 92037, USA

    Karen E. Nelson

  3. Western Connecticut Health Network, 24 Hospital Avenue, Danbury, CT, 06810, USA

    Joann Petrini

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Contributions

YY, responsible for LC-MS/MS experiments and LC-MS/MS data analysis, participation in writing manuscript; HS, responsible for biostatistical data and network analyses, graphic art work, participation in writing manuscript; KK, responsible for cytokine array experiments and data analysis; TT, sample preparation to analyze urinary proteomes; JP, design, organization, and implementation of human subject recruitment and medical data collection; KEN, conceptualization of the study and manuscript review; RP, conceptualization and implementation of the study, biological data analysis, wrote manuscript.

Corresponding author

Correspondence to Rembert Pieper.

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The authors declare that they have no conflicts of interest.

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Internal review boards (IRB) of Danbury Hospital and the J. Craig Venter Institute (JCVI), Rockville, MD approved a consent form and human subject protocol outlining risks and benefits of participation in 2013. JP and RP wrote the consent form and human subject protocol.

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All human subjects consented to participate and enable specimen and medical data collections.

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Supplemental File S1

Dataset: Relative abundances of Blood Plasma Cytokines and Chemokines from 124 Specimens (65 Human Subjects) for "Healthy Aging" and "Non-Healthy Aging" Cohorts (XLSX 74 kb)

Supplemental File S2

Dataset: Urinary Proteome Datasets from 125 Specimens (65 Human Subjects) for "Healthy Aging" and "Non-Healthy Aging" Cohorts (XLSX 473 kb)

Supplemental File 3

Dataset: Medical Histories for the 65 Study Participants and their Differentiation into "Healthy Aging" and "Non-Healthy Aging" Cohorts (XLSX 28 kb)

Supplemental File S4

Figure: Pearson correlation analysis generates hierarchical clusters of urinary proteome datasets (PNG 1691 kb)

High Resolution Image (TIF 356 kb)

Supplemental File S5

Table: Differentially Abundant Proteins Comparing Healthy Aging (HA) and Non-Healthy Aging (NHA) Cohorts Based on Urinary Proteome Analysis. (DOCX 33 kb)

Supplemental File S6

Figure: Blood Plasma Cytokine Abundance Profiles from 65 Human Subjects Assigned to Healthy Aging and Non-Healthy Aging Cohorts Analyzed Clustered Using the Euclidian Clustering Algorithm. (PNG 2074 kb)

High Resolution Image (TIF 822 kb)

Supplemental File S7

Figure: Correlation Analysis for Differentially Abundant Cytokines and Chemokines (Healthy Aging vs. Non-Healthy Aging Cohorts) (PNG 1695 kb)

High Resolution Image (TIF 574 kb)

Supplemental File S8

Dataset: Pathway Enrichment Analysis Using GO and KEGG Terms Based on Statistically Significant Proteins in the Urinary Proteome Survey (p-value < 0.05) Comparing the Healthy Aging (HA) and Non-Healthy Aging (NHA) Cohorts. (XLSX 56 kb)

Supplemental File S9

Figure: GO term and KEGG pathway enrichment with associated protein network based on proteins decreased in abundance in the HA versus the NHA cohort (HA vs. NHA; p-value < 0.05). (PNG 677 kb)

High Resolution Image (TIF 175 kb)

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Yu, Y., Singh, H., Kwon, K. et al. Protein signatures from blood plasma and urine suggest changes in vascular function and IL-12 signaling in elderly with a history of chronic diseases compared with an age-matched healthy cohort. GeroScience 43, 593–606 (2021). https://doi.org/10.1007/s11357-020-00269-y

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