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Status: Bibliographieeintrag

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Verfasst von:Tappu, Rewati [VerfasserIn]   i
 Haas, Jan [VerfasserIn]   i
 Lehmann, David Hermann [VerfasserIn]   i
 Sedaghat-Hamedani, Farbod [VerfasserIn]   i
 Kayvanpour, Elham [VerfasserIn]   i
 Keller, Andreas [VerfasserIn]   i
 Katus, Hugo [VerfasserIn]   i
 Frey, Norbert [VerfasserIn]   i
 Meder, Benjamin [VerfasserIn]   i
Titel:Multi-omics assessment of dilated cardiomyopathy using non-negative matrix factorization
Verf.angabe:Rewati Tappu, Jan Haas, David H. Lehmann, Farbod Sedaghat-Hamedani, Elham Kayvanpour, Andreas Keller, Hugo A. Katus, Norbert Frey, Benjamin Meder
E-Jahr:2022
Jahr:August 18, 2022
Umfang:26 S.
Fussnoten:Gesehen am 21.04.2023
Titel Quelle:Enthalten in: PLOS ONE
Ort Quelle:San Francisco, California, US : PLOS, 2006
Jahr Quelle:2022
Band/Heft Quelle:17(2022), 8 vom: Aug., Artikel-ID e0272093, Seite 1-26
ISSN Quelle:1932-6203
Abstract:Dilated cardiomyopathy (DCM), a myocardial disease, is heterogeneous and often results in heart failure and sudden cardiac death. Unavailability of cardiac tissue has hindered the comprehensive exploration of gene regulatory networks and nodal players in DCM. In this study, we carried out integrated analysis of transcriptome and methylome data using non-negative matrix factorization from a cohort of DCM patients to uncover underlying latent factors and covarying features between whole-transcriptome and epigenome omics datasets from tissue biopsies of living patients. DNA methylation data from Infinium HM450 and mRNA Illumina sequencing of n = 33 DCM and n = 24 control probands were filtered, analyzed and used as input for matrix factorization using R NMF package. Mann-Whitney U test showed 4 out of 5 latent factors are significantly different between DCM and control probands (P<0.05). Characterization of top 10% features driving each latent factor showed a significant enrichment of biological processes known to be involved in DCM pathogenesis, including immune response (P = 3.97E-21), nucleic acid binding (P = 1.42E-18), extracellular matrix (P = 9.23E-14) and myofibrillar structure (P = 8.46E-12). Correlation network analysis revealed interaction of important sarcomeric genes like Nebulin, Tropomyosin alpha-3 and ERC-protein 2 with CpG methylation of ATPase Phospholipid Transporting 11A0, Solute Carrier Family 12 Member 7 and Leucine Rich Repeat Containing 14B, all with significant P values associated with correlation coefficients >0.7. Using matrix factorization, multi-omics data derived from human tissue samples can be integrated and novel interactions can be identified. Hypothesis generating nature of such analysis could help to better understand the pathophysiology of complex traits such as DCM.
DOI:doi:10.1371/journal.pone.0272093
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.1371/journal.pone.0272093
 Volltext: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0272093
 DOI: https://doi.org/10.1371/journal.pone.0272093
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:DNA methylation
 Extracellular matrix
 Factor analysis
 Gene expression
 Gene ontologies
 Genetic networks
 Hierarchical clustering
 Treatment guidelines
K10plus-PPN:1843347237
Verknüpfungen:→ Zeitschrift

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