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Human plasma proteomic profiles indicative of cardiorespiratory fitness

An Author Correction to this article was published on 27 August 2021

Abstract

Maximal oxygen uptake (VO2max) is a direct measure of human cardiorespiratory fitness and is associated with health. However, the molecular determinants of interindividual differences in baseline (intrinsic) VO2max, and of increases of VO2max in response to exercise training (ΔVO2max), are largely unknown. Here, we measure ~5,000 plasma proteins using an affinity-based platform in over 650 sedentary adults before and after a 20-week endurance-exercise intervention and identify 147 proteins and 102 proteins whose plasma levels are associated with baseline VO2max and ΔVO2max, respectively. Addition of a protein biomarker score derived from these proteins to a score based on clinical traits improves the prediction of an individual’s ΔVO2max. We validate findings in a separate exercise cohort, further link 21 proteins to incident all-cause mortality in a community-based cohort and reproduce the specificity of ~75% of our key findings using antibody-based assays. Taken together, our data shed light on biological pathways relevant to cardiorespiratory fitness and highlight the potential additive value of protein biomarkers in identifying exercise responsiveness in humans.

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Fig. 1: Proteins associated with baseline VO2max among offspring and parents.
Fig. 2: Plasma proteins associated with baseline and ΔVO2max.
Fig. 3: Muscle proteins positively associated with baseline VO2max.
Fig. 4: GSEA for proteins associated with ΔVO2max or baseline VO2max.
Fig. 5: ROC curves for relative VO2max changes with exercise training > 15%.
Fig. 6: Spearman’s correlations between aptamer-based and antibody-based assays among top findings.

Data availability

Deidentified, individual-level proteomics and phenotypic data that support the HERITAGE findings within this paper are available at https://motrpac-data.org/related-studies/heritage-proteomics. Overlapping aptamer-based and antibody-based proteomics data on the HERITAGE sample are included Supplementary Data Table 1. GWAS summary statistics for FHS and JHS are available through restricted access via the database of Genotypes and Phenotypes (dbGaP), a publicly available resource developed to archive data from human studies of genotype–phenotype relationships and can be accessed here (https://www.ncbi.nlm.nih.gov/gap/; FHS accession number: phs000363.v19.p13; JHS accession number: phs000964). FHS proteomics data have also been deposited in dbGaP and are available through the same accession number. JHS proteomics data have been deposited in the JHS Data Coordinating Center and are being deposited in dbGaP (accession number: phs002256.v1.p1); pending its receipt in dbGaP, all JHS data are available from the JHS Data Coordinating Center on request (JHSccdc@umc.edu). In addition, proteogenetics findings (precise SNP IDs) included in Supplementary Table 15 from FHS/MDCS meta-analysis and JHS have been provided in Tables 2 and 3 in the Supplementary Data, respectively. Additional data supporting the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This study is supported by the National Institute of Health grants K23 HL150327-01A1 (J.M.R.); R01 HL132320; HL133870 (R.E.G.); U24 DK112340 (R.E.G., S.A.C.), R01 HL45670, HL47317, HL47321, HL47323 and HL47327 (all in support of the HERITAGE Family Study); NR019628 (M.A.S., R.E.G.); and HL146462 (M.A.S.). C.B. is partially funded by the John W. Barton Sr. Chair in Genetics and Nutrition. S.G. and C.B. are partially supported by the NIH-funded COBRE grant (NIH 8 P30GM118430-01). S.G. is supported in part by 2 U54 GM104940 from the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health, which funds the Louisiana Clinical and Translational Science Center. This research was also supported by the National Medical Research Council, Ministry of Health, Singapore (WBS R913200076263) to S.G. D.S. is supported with a doctoral scholarship from the German Academic Scholarship Foundation (Studienstiftung des deutschen Volkes).

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Contributions

J.M.R., M.A.S., C.B. and R.E.G. conceptualized the study. J.M.R., B.P., D.S., T.R., S.D., M.J.K., C.S., P.M.J.B, R.R. and R.E.G designed research, performed biochemical experiments and analysed the proteomics data. J.M.R., U.A.T. and D.H.K. performed genetics analyses. J.L.B., C.B., S.A.C., S.G. and L.L.J. provided technical assistance and/or conceptual advice. J.M.R. and R.E.G. wrote the manuscript with assistance from the coauthors.

Corresponding author

Correspondence to Robert E. Gerszten.

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Competing interests

S.A.C. is a member of the scientific advisory boards of Kymera, PTM BioLabs and Seer and is a scientific advisor to Pfizer and Biogen. The other authors declare no competing interests.

Additional information

Peer review information Nature Metabolism thanks Manuel Mayr and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Christoph Schmitt; Pooja Jha.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Secreted proteins positively related to bone homeostasis and baseline VO2max.

Functional representation of proteins‘ role in bone metabolism and homeostasis. Left and middle: SMOC1 regulates osteoblast differentiation. BMPs are related to bone formation via the TGF-ß pathway and are mediated by extracellular signalling molecules such as NOG. Right: simplified schematic of proteins related to cartilage formation and their location within cartilage tissue.

Extended Data Fig. 2 Receiver-operating characteristic curve for relative VO2max changes with exercise training > 15% using overlapping targets between aptamer- and antibody-based proteomic platforms.

7/10 overlapping proteins on both platforms demonstrated moderate-strong correlation (SELE, TCL1A, COMP, CREG1, STC1, IL1RL2, LILRA2; ρ = 0.41–0.91) and were used in modeling.

Supplementary information

Reporting Summary

Supplementary Tables

Supplementary Tables 1–15

Supplementary Data

Aptamer-based (SOMAscan) and antibody-based (Olink) assays for the HERITAGE subset

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Robbins, J.M., Peterson, B., Schranner, D. et al. Human plasma proteomic profiles indicative of cardiorespiratory fitness. Nat Metab 3, 786–797 (2021). https://doi.org/10.1038/s42255-021-00400-z

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