Multi-omics assessment of dilated cardiomyopathy using non-negative matrix factorization

• Published in: PloS one Vol. 17; no. 8; p. e0272093
• Main Authors: Tappu, Rewati, Haas, Jan, Lehmann, David H., Sedaghat-Hamedani, Farbod, Kayvanpour, Elham, Keller, Andreas, Katus, Hugo A., Frey, Norbert, Meder, Benjamin
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 18.08.2022; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Biological activity; Biology and life sciences; Biopsy; Cardiomyopathy; Cardiomyopathy, Dilated; Cardiovascular disease; Clustering; Computer and Information Sciences; Computer-aided medical diagnosis; Congestive heart failure; Correlation; Correlation coefficient; Correlation coefficients; CpG islands; Data analysis; Datasets; Decomposition; Deoxyribonucleic acid; Diagnosis; Dilated cardiomyopathy; DNA; DNA methylation; DNA Methylation - genetics; Extracellular matrix; Factorization; Gene expression; Gene sequencing; Genetic aspects; Genomes; Heart; High-Throughput Nucleotide Sequencing; Human tissues; Humans; Immune response; Leucine; Medicine and Health Sciences; Methods; Methylation; Network analysis; Nucleic acids; Pathogenesis; Patients; Phospholipids; Physical Sciences; Research and Analysis Methods; RNA sequencing; Sarcomeres - metabolism; Tissues; Transcriptomes; Tropomyosin; Variables; Germany
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0272093

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.