ArticleJournal of proteome research2020
Identification of Putative Early Atherosclerosis Biomarkers by Unsupervised Deconvolution of Heterogeneous Vascular Proteomes.
Article in Journal of proteome research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 28 citations in OpenAlex.
- Proteomic analysis of oxidative modifications in human atherosclerotic plaques and control arteries.Redox biology · 2026Article
- Molecular mechanism leading to human coronary atherosclerosis assessed by proteomic analysis and RNA sequences.European heart journal · 2026Article
- Novel driver gene MDC1 confers homologous recombination repair deficiency and genomic instability in chemoresistant relapsing ovarian cancer.Journal of translational medicine · 2026Article
- Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer.Journal of proteome research · 2025Article
- Embracing the informative missingness and silent gene in analyzing biologically diverse samples.Scientific reports · 2024Article
- ABDS: a bioinformatics tool suite for analyzing biologically diverse samples.Research square · 2024Article
- Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges.Nucleic acids research · 2024Review
- CAM3.0: determining cell type composition and expression from bulk tissues with fully unsupervised deconvolution.Bioinformatics (Oxford, England) · 2024Article
- Proteomic analysis of the extracellular matrix of human atherosclerotic plaques shows marked changes between plaque types.Matrix biology plus · 2024Article
- Uncovering Protein Networks in Cardiovascular Proteomics.Molecular & cellular proteomics : MCP · 2023Review
- Comparative assessment and novel strategy on methods for imputing proteomics data.Scientific reports · 2022Article
- Proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection.JVS-vascular science · 2022Article
- COT: an efficient and accurate method for detecting marker genes among many subtypes.Bioinformatics advances · 2022Article
- Cosbin: cosine score-based iterative normalization of biologically diverse samples.Bioinformatics advances · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 5 institutions in 1 country.
Funding
Abstract
Coronary artery disease remains a leading cause of death in industrialized nations, and early detection of disease is a critical intervention target to effectively treat patients and manage risk. Proteomic analysis of mixed tissue homogenates may obscure subtle protein changes that occur uniquely in underlying tissue subtypes. The unsupervised 'convex analysis of mixtures' (CAM) tool has previously been shown to effectively segregate cellular subtypes from mixed expression data. In this study, we hypothesized that CAM would identify proteomic information specifically informative to early atherosclerosis lesion involvement that could lead to potential markers of early disease detection. We quantified the proteome of 99 paired abdominal aorta (AA) and left anterior descending coronary artery (LAD) specimens (N = 198 specimens total) acquired during autopsy of young adults free of diagnosed cardiac disease. The CAM tool was then used to segregate protein subsets uniquely associated with different underlying tissue types, yielding markers of normal and fibrous plaque (FP) tissues in LAD and AA (N = 62 lesions markers). CAM-derived FP marker expression was validated against pathologist estimated luminal surface involvement of FP, as well as in an orthogonal cohort of "pure" fibrous plaque, fatty streak, and normal vascular specimens. A targeted mass spectrometry (MS) assay quantified 39 of 62 CAM-FP markers in plasma from women with angiographically verified coronary artery disease (CAD, N = 46) or free from apparent CAD (control, N = 40). Elastic net variable selection with logistic regression reduced this list to 10 proteins capable of classifying CAD status in this cohort with <6% misclassification error, and a mean area under the receiver operating characteristic curve of 0.992 (confidence interval 0.968-0.998) after cross validation. The proteomics-CAM workflow identified lesion-specific molecular biomarker candidates by distilling the most representative molecules from heterogeneous tissue types.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.