Targeted Plasma Proteomics to Predict the Development of Carotid Plaques

Review Cardiac & Cardiovascular Systems

Systems biology in cardiovascular disease: a multiomics approach

Abhishek Joshi et al.

Summary: Omics techniques generate large, multidimensional data that can be analyzed using informatics approaches and traditional statistical methods. Systems biology, utilizing network analysis and machine learning, addresses the complexity of biological processes. Novel approaches combining gene regulatory networks, proteomics, metabolomics, lipidomics, and phenomics with informatics techniques provide new insights into cardiovascular disease.

NATURE REVIEWS CARDIOLOGY (2021)

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Article Hematology

Plasma Protein Profile of Carotid Artery Atherosclerosis and Atherosclerotic Outcomes Meta-Analyses and Mendelian Randomization Analyses

Lars Lind et al.

Summary: This study identified several proteins related to carotid atherosclerosis, showing differences in their association with IMT-CCA, plaque, and incident atherosclerotic disease.

ARTERIOSCLEROSIS THROMBOSIS AND VASCULAR BIOLOGY (2021)

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Article Cardiac & Cardiovascular Systems

Proteomics-Enabled Deep Learning Machine Algorithms Can Enhance Prediction of Mortality

Matthias Unterhuber et al.

Summary: In patients with cardiovascular risk factors, machine-learning models based on proteomics outperform traditional regression models and clinical scores for predicting all-cause mortality.

JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY (2021)

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Article Cardiac & Cardiovascular Systems