David M Herrington1, Chunhong Mao2, Sarah J Parker3, Zongming Fu4, Guoqiang Yu5, Lulu Chen5, Vidya Venkatraman3, Yi Fu5, Yizhi Wang5, Timothy D Howard6, Goo Jun7, Caroline F Zhao8, Yongmei Liu9, Georgia Saylor8, Weston R Spivia3, Grace B Athas10, Dana Troxclair10, James E Hixson7, Richard S Vander Heide10, Yue Wang5, Jennifer E Van Eyk3. 1. Section on Cardiovascular Medicine, Department of Internal Medicine (D.M.H., C.F.Z., G.S.) dherring@wakehealth.edu. 2. Biocomplexity Institute of Virginia Tech, Virginia Tech, Blacksburg (C.M.). 3. Advanced Clinical Biosystems Research Institute, Cedars-Sinai Heart Institute, and Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA (S.T.P., V.V., W.R.S., J.E.V.E.). 4. Johns Hopkins Medical Institute, Baltimore, MD (Z.F.). 5. Department of Electrical and Computer Engineering, Virginia Tech, Arlington (G.Y., L.C., Y.F., Yizhi Wang, Yue Wang). 6. Department of Biochemistry (T.D.H.). 7. Department of Epidemiology, Human Genetics and Environmental Sciences, Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston (G.J., J.E.H.). 8. Section on Cardiovascular Medicine, Department of Internal Medicine (D.M.H., C.F.Z., G.S.). 9. Department of Epidemiology, Division of Public Health Sciences (Y.L.), Wake Forest School of Medicine, Winston-Salem, NC. 10. Department of Pathology, Louisiana State Health Science Center, New Orleans (G.B.A., D.T., R.C.V.H.).
Abstract
BACKGOUND: The inability to detect premature atherosclerosis significantly hinders implementation of personalized therapy to prevent coronary heart disease. A comprehensive understanding of arterial protein networks and how they change in early atherosclerosis could identify new biomarkers for disease detection and improved therapeutic targets. METHODS: Here we describe the human arterial proteome and proteomic features strongly associated with early atherosclerosis based on mass spectrometry analysis of coronary artery and aortic specimens from 100 autopsied young adults (200 arterial specimens). Convex analysis of mixtures, differential dependent network modeling, and bioinformatic analyses defined the composition, network rewiring, and likely regulatory features of the protein networks associated with early atherosclerosis and how they vary across 2 anatomic distributions. RESULTS: The data document significant differences in mitochondrial protein abundance between coronary and aortic samples (coronary>>aortic), and between atherosclerotic and normal tissues (atherosclerotic<<normal), and major alterations in tumor necrosis factor, insulin receptor, peroxisome proliferator-activated receptor-α, and peroxisome proliferator-activated receptor-γ protein networks, as well, in the setting of early disease. In addition, a subset of tissue protein biomarkers indicative of early atherosclerosis was shown to predict anatomically defined coronary atherosclerosis when measured in plasma samples in a separate clinical cohort (area under the curve=0.92 [0.83-0.96]), thereby validating the use of human tissue proteomics to discover relevant plasma biomarkers for clinical applications. In addition to the specific proteins and pathways identified here, the publicly available data resource and the analysis pipeline used illustrate a strategy for interrogating and interpreting the proteomic architecture of tissues that may be relevant for other chronic diseases characterized by multicellular tissue phenotypes. CONCLUSIONS: The human arterial proteome can be viewed as a complex network whose architectural features vary considerably as a function of anatomic location and the presence or absence of atherosclerosis. The data suggest important reductions in mitochondrial protein abundance in early atherosclerosis and also identify a subset of plasma proteins that are highly predictive of angiographically defined coronary disease.
BACKGOUND: The inability to detect premature atherosclerosis significantly hinders implementation of personalized therapy to prevent coronary heart disease. A comprehensive understanding of arterial protein networks and how they change in early atherosclerosis could identify new biomarkers for disease detection and improved therapeutic targets. METHODS: Here we describe the human arterial proteome and proteomic features strongly associated with early atherosclerosis based on mass spectrometry analysis of coronary artery and aortic specimens from 100 autopsied young adults (200 arterial specimens). Convex analysis of mixtures, differential dependent network modeling, and bioinformatic analyses defined the composition, network rewiring, and likely regulatory features of the protein networks associated with early atherosclerosis and how they vary across 2 anatomic distributions. RESULTS: The data document significant differences in mitochondrial protein abundance between coronary and aortic samples (coronary>>aortic), and between atherosclerotic and normal tissues (atherosclerotic<<normal), and major alterations in tumornecrosis factor, insulin receptor, peroxisome proliferator-activated receptor-α, and peroxisome proliferator-activated receptor-γ protein networks, as well, in the setting of early disease. In addition, a subset of tissue protein biomarkers indicative of early atherosclerosis was shown to predict anatomically defined coronary atherosclerosis when measured in plasma samples in a separate clinical cohort (area under the curve=0.92 [0.83-0.96]), thereby validating the use of human tissue proteomics to discover relevant plasma biomarkers for clinical applications. In addition to the specific proteins and pathways identified here, the publicly available data resource and the analysis pipeline used illustrate a strategy for interrogating and interpreting the proteomic architecture of tissues that may be relevant for other chronic diseases characterized by multicellular tissue phenotypes. CONCLUSIONS: The human arterial proteome can be viewed as a complex network whose architectural features vary considerably as a function of anatomic location and the presence or absence of atherosclerosis. The data suggest important reductions in mitochondrial protein abundance in early atherosclerosis and also identify a subset of plasma proteins that are highly predictive of angiographically defined coronary disease.
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