Aptamer-Based Proteomic Profiling Reveals Novel Candidate Biomarkers and Pathways in Cardiovascular Disease.

Circulation

From Division of Pulmonary and Critical Care Medicine, Department of Medicine (D.N.) and the Cardiovascular Research Center (D.N., S.S., D.S., M.J.K., X.S., M.D.B., J.F.O., L.A.F., R.E.G.), Massachusetts General Hospital, Harvard Medical School, Boston; Broad Institute of MIT and Harvard, Cambridge, MA (E.W.K., H.K., S.A.C., R.E.G.); Cardiovascular Division, Brigham and Women's Hospital, Boston, MA (M.D.B., M.S.S.); Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston (M.A.F., M.S.S., R.E.G.); Preventive Medicine Section, Department of Medicine, Boston University School of Medicine, MA (R.S.V.); Department of Biostatistics, Boston University School of Public Health, MA (M.G.L.); The National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA (M.G.L.); Division of Cardiovascular Medicine, Vanderbilt University, Nashville, TN (T.J.W.); and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (R.E.G.).

Published: July 2016

Background: Single-stranded DNA aptamers are oligonucleotides of ≈50 base pairs in length selected for their ability to bind proteins with high specificity and affinity. Emerging DNA aptamer-based technologies may address limitations of existing proteomic techniques, including low sample throughput, which have hindered proteomic analyses of large cohorts.

Methods: To identify early biomarkers of myocardial injury, we applied an aptamer-based proteomic platform that measures 1129 proteins to a clinically relevant perturbational model of planned myocardial infarction (PMI), patients undergoing septal ablation for hypertrophic cardiomyopathy. Blood samples were obtained before and at 10 and 60 minutes after PMI, and protein changes were assessed by repeated-measures analysis of variance. The generalizability of our PMI findings was evaluated in a spontaneous myocardial infarction cohort (Wilcoxon rank-sum). We then tested the platform's ability to detect associations between proteins and Framingham Risk Score components in the Framingham Heart Study, performing regression analyses for each protein versus each clinical trait.

Results: We found 217 proteins that significantly changed in the peripheral vein blood after PMI in a derivation cohort (n=15; P<5.70E-5). Seventy-nine of these proteins were validated in an independent PMI cohort (n=15; P<2.30E-4); >85% were directionally consistent and reached nominal significance. We detected many protein changes that are novel in the context of myocardial injury, including Dickkopf-related protein 4, a WNT pathway inhibitor (peak increase 124%, P=1.29E-15) and cripto, a growth factor important in cardiac development (peak increase 64%, P=1.74E-4). Among the 40 validated proteins that increased within 1 hour after PMI, 23 were also elevated in patients with spontaneous myocardial infarction (n=46; P<0.05). Framingham Heart Study analyses revealed 156 significant protein associations with the Framingham Risk Score (n=899), including aminoacylase 1 (β=0.3386, P=2.54E-22) and trigger factor 2 (β=0.2846, P=5.71E-17). Furthermore, we developed a novel workflow integrating DNA-based immunoaffinity with mass spectrometry to analytically validate aptamer specificity.

Conclusions: Our results highlight an emerging proteomics tool capable of profiling >1000 low-abundance analytes with high sensitivity and high precision, applicable both to well-phenotyped perturbational studies and large human cohorts, as well.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4963294PMC
http://dx.doi.org/10.1161/CIRCULATIONAHA.116.021803DOI Listing

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