ReviewThe Journal of clinical investigation2020
The application of big data to cardiovascular disease: paths to precision medicine.
Review in The Journal of clinical investigation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 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
50 citing papers in PubMed.
- Targeting bromodomain and extraterminal proteins in cardiovascular disease: Pathological mechanisms and therapeutic applications.The Journal of international medical research · 2026Review
- Systems Biology Identifies TARS2 as a Cardiomyocyte Regulator of Mitochondrial Oxidative Stress in Dilated Cardiomyopathy.JACC. Basic to translational science · 2026Article
- Precision Medicine Through Network Language: Integrating Clinical Insight and Data Expertise.Genes · 2026Review
- Special Issue "Molecular Advances in Heart Disease: Genomics, Proteomics, and Bioinformatics of Heart Research".International journal of molecular sciences · 2025Article
- Integrating Large-Scale Data Analytics for Cardiovascular Disease Prediction: A Scoping Review.Healthcare informatics research · 2025Article
- Bottlenecks in advancing and applying multiomic data integration-common data resources as rate-limiting drivers-the high-impact use case of atherosclerotic cardiovascular disease.Briefings in bioinformatics · 2025Review
- Revolutionizing Utility of Big Data Analytics in Personalized Cardiovascular Healthcare.Bioengineering (Basel, Switzerland) · 2025Review
- Big data for neuroscience in the context of predictive, preventive, and personalized medicine.The EPMA journal · 2025Review
- Precision cardiovascular medicine: shifting the innovation paradigm.Frontiers in science · 2025Article
- Molecular Study of Sudden Cardiac Death.International journal of molecular sciences · 2024Article
- Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision medicine.Scientific reports · 2024Article
- Seasonal variations of the prevalence of metabolic syndrome and its markers using big-data of health check-ups.Environmental health and preventive medicine · 2024Article
- A machine learning based approach to identify carotid subclinical atherosclerosis endotypes.Cardiovascular research · 2023Article
- Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases.Scientific reports · 2023Article
- Multiomics Network Medicine Approaches to Precision Medicine and Therapeutics in Cardiovascular Diseases.Arteriosclerosis, thrombosis, and vascular biology · 2023Review
- Lacking mechanistic disease definitions and corresponding association data hamper progress in network medicine and beyond.Nature communications · 2023Article
- Proline and glucose metabolic reprogramming supports vascular endothelial and medial biomass in pulmonary arterial hypertension.JCI insight · 2023Article
- Tensions in Taxonomies: Current Understanding and Future Directions in the Pathobiologic Basis and Treatment of Group 1 and Group 3 Pulmonary Hypertension.Comprehensive Physiology · 2023Review
- Uncovering common pathobiological processes between COVID-19 and pulmonary arterial hypertension by integrating Omics data.Pulmonary circulation · 2023Article
- Subtyping based on immune cell fractions reveal heterogeneity of cardiac fibrosis in end-stage heart failure.Frontiers in immunology · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Advanced phenotyping of cardiovascular diseases has evolved with the application of high-resolution omics screening to populations enrolled in large-scale observational and clinical trials. This strategy has revealed that considerable heterogeneity exists at the genotype, endophenotype, and clinical phenotype levels in cardiovascular diseases, a feature of the most common diseases that has not been elucidated by conventional reductionism. In this discussion, we address genomic context and (endo)phenotypic heterogeneity, and examine commonly encountered cardiovascular diseases to illustrate the genotypic underpinnings of (endo)phenotypic diversity. We highlight the existing challenges in cardiovascular disease genotyping and phenotyping that can be addressed by the integration of big data and interpreted using novel analytical methodologies (network analysis). Precision cardiovascular medicine will only be broadly applied to cardiovascular patients once this comprehensive data set is subjected to unique, integrative analytical strategies that accommodate molecular and clinical heterogeneity rather than ignore or reduce it.
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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.