Endotyping in Heart Failure ― Identifying Mechanistically Meaningful Subtypes of Disease ―
Open Access
- 25 August 2021
- journal article
- review article
- Published by Japanese Circulation Society in Circulation Journal
- Vol. 85 (9), 1407-1415
- https://doi.org/10.1253/circj.cj-21-0349
Abstract
Endotyping is an emerging concept in which diseases are classified into distinct subtypes based on underlying molecular mechanisms. Heart failure (HF) is a complex clinical syndrome that encompasses multiple endotypes with differential risks of adverse events, and varying responses to treatment. Identifying these distinct endotypes requires molecular-level investigation involving multi-“omics” approaches, including genomics, transcriptomics, proteomics, and metabolomics. The derivation of these HF endotypes has important implications in promoting individualized treatment and facilitating more targeted selection of patients for clinical trials, as well as in potentially revealing new pathways of disease that may serve as therapeutic targets. One challenge in the integrated analysis of high-throughput omics and detailed clinical data is that it requires the ability to handle “big data”, a task for which machine learning is well suited. In particular, unsupervised machine learning has the ability to uncover novel endotypes of disease in an unbiased approach. In this review, we will discuss recent efforts to identify HF endotypes and cover approaches involving proteomics, transcriptomics, and genomics, with a focus on machine-learning methods.Keywords
This publication has 54 references indexed in Scilit:
- Phenomapping for Novel Classification of Heart Failure With Preserved Ejection FractionCirculation, 2015
- Clinical Implications of Chronic Heart Failure Phenotypes Defined by Cluster AnalysisJournal of the American College of Cardiology, 2014
- Circulating Long Noncoding RNA, LIPCAR, Predicts Survival in Patients With Heart FailureCirculation Research, 2014
- Association of Genome-Wide Variation With Highly Sensitive Cardiac Troponin-T Levels in European Americans and BlacksCirculation: Cardiovascular Genetics, 2013
- Genetics of inherited cardiomyopathyEuropean Heart Journal, 2011
- Genome-wide association analysis and fine mapping of NT-proBNP level provide novel insight into the role of the MTHFR-CLCN6-NPPA-NPPB gene clusterHuman Molecular Genetics, 2011
- Identification of a Gene Expression Profile That Differentiates Between Ischemic and Nonischemic CardiomyopathyCirculation, 2004
- Use of Gene-Expression Profiling to Identify Prognostic Subclasses in Adult Acute Myeloid LeukemiaThe New England Journal of Medicine, 2004
- Model-Based Clustering, Discriminant Analysis, and Density EstimationJournal of the American Statistical Association, 2002
- Estimating the Number of Clusters in a Data Set Via the Gap StatisticJournal of the Royal Statistical Society Series B: Statistical Methodology, 2001