Genomic Analysis of Left Ventricular Remodeling
Abstract
T he left ventricle (LV) of the heart remodels in response to hemodynamic load through the processes of physiological or pathophysiological hypertrophy.[1][2][3] Despite extensive study of the molecular basis of cardiac hypertrophy and LV remodeling, 1,4 the mainstay of medical treatment of maladaptive remodeling remains based on therapies initially devised for treating hypertension.The limited progress in the development of specific therapies for LV remodeling has led some to refer to "the impossible task of developing a new treatment for heart failure" and is the reason why, in part, device therapies have received such recent attention.[5][6][7][8] To gain a better understanding of the biology of maladaptive LV remodeling, with a view to identifying therapeutic targets, new paradigms and experimental approaches are needed, and genomics provides one such methodology.Genomics is the study of genome-scale data sets, at the DNA or RNA level, and when combined with studies of physiological traits or disease phenotypes, genomics can be used to infer molecular insights.Unlike single-gene studies, which are the favored hypothesis-driven design, 4 genomic approaches examine variation in up to gigabases of sequences to find statistical associations between transcripts and traits in a hypothesis-free system.These hypothesis-free studies have often been criticized as unfocused, but following the successes of genome-wide association studies (GWAS) and the recent achievements of integrated genetic and genomic analyses, a new era of genomic experimentation presents itself.9 -14 It is notable that GWAS and integrated genomic studies in humans often identify regions associated with disease rather than specific genes and that effect sizes are small; nevertheless, these data remain highly informative.[15][16][17] In this article, we review the genomic analysis of LV remodeling in the context of the recent past, the state of the art, and the imminent use of next-generation sequencing.A glossary of terms is provided in Table 1.
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For studies of disease, co-expression networks can be constructed based on variations in gene expression that occur among control and affected individuals separately.
“For studies of disease, co-expression networks can be constructed based on variations in gene expression that occur among control and affected individuals separately [72–74].”
From Multi-omics approaches to disease (2017) · cites this paper as [74]
Integration of genetic information with network modeling has been used to highlight pathways that contribute to disease and to identify key drivers in biologic processes.
“Such integration of genetic information with network modeling has been used to highlight pathways that contribute to disease and to identify “key drivers” in biologic processes [72–74, 78].”
From Multi-omics approaches to disease (2017) · cites this paper as [74]
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Multi-omics approaches to disease
Hasin, Y., Seldin, M., & Lusis, A. (2017) · Genome Biology · doi:10.1186/s13059-017-1215-1 · Cited by 2,953 · see citing works
- Authors
- Sarwar, R., & Cook, S. A.
- Affiliations
- Imperial College London (GB)
- Venue
- Circulation
- Published
- 2009-08-04
- Volume
- 120
- Issue
- 5
- Pages
- 437-444
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- OpenAlex
- W2117355278
- Cited by
- 13
- References
- 104
- Citations by year
- 2024: 1 · 2023: 1 · 2017: 2 · 2016: 1 · 2014: 1 · 2012: 1
- FWCI
- 1.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Circulation (publishedVersion)
- PubMed (publishedVersion)
- National University of Singapore (submittedVersion)
- Funders
- British Heart Foundation
- Fondation Leducq
- Medical Research Council
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac Fibrosis and Remodeling
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiomyopathy and Myosin Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Signaling Pathways in Disease
- Keywords
- left ventricular remodeling, cardiac hypertrophy, maladaptive remodeling, heart failure, genome-wide association study, integrative genomics, next-generation sequencing, therapeutic target, hemodynamic load
- MeSH terms
- Cardiovascular Diseases, Humans, Ventricular Remodeling, Gene Expression Profiling, Genomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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