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

Tappu, Rewati; Haas, Jan; Lehmann, David; Sedaghat‐Hamedani, Farbod; Kayvanpour, Elham; Keller, Andreas; Katus, Hugo A.; Frey, Norbert; Meder, Benjamin

doi:10.1371/journal.pone.0272093

Cited by 6 publications

(2 citation statements)

References 63 publications

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“…DCM is a heterogeneous genetically-related disease that is characterized by enlarged ventricles and reduced function, often leading to heart failure and sudden cardiac death [14,15]. The prevalence of DCM may vary according to geographic and ethnic differences and diagnosis criteria.…”

Section: Discussionmentioning

confidence: 99%

Multiple effect mechanisms of FLNC in dilated cardiomyopathy based on genetic variants, transcriptomics, and immune infiltration analysis

Cai

et al. 2023

Preprint

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Background: In recent years, the FLNC gene has been shown to participate in dilated cardiomyopathy (DCM) through different mechanisms, and its variants are a common cause of hereditary DCM. This study aimed to systematically evaluate multiple FLNC effect mechanisms in DCM and to expand the spectrum of FLNC gene variations. Methods:Based on five microarray expression profile datasets downloaded from the Gene Expression Omnibus (GEO) database, comprising DCM tissue and healthy control groups, the difference in FLNC gene expression levels between the two groups was evaluated. Subsequently, differentially expressed genes (DEGs) among 81 DCM tissues were identified based on FLNC grouping, and gene ontology, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, correlation analysis, and protein–protein interaction (PPI) network construction were conducted for DEGs. Based on single-sample Gene Set Enrichment Analysis method, we then evaluated differences in immune infiltration levels between the two groups using ''student 's'' and the correlation between FLNC gene expression.and the immune cells we using '' Spearman's correlation '' methods. Then, we constructed a ce-RNA network of FLNC based on several databases.Finally,100 blood samples from DCM and non-DCM individuals from the Guangxi Zhuang population in China were selected for FLNC gene sequencing, case-specific newly discovered or rare FLNC gene mutation sites were screened, and the clinical information of patients with FLNC gene mutations and their families were collected for Sanger sequencing verification. Results: FLNC expression was significantly higher in the DCM group than in the control group. After grouping 81 DCM tissues according to median FLNC expression levels, 54 DEGs were identified. The enrichment analysis shows that downregulated DEGs were more associated with inflammation and immunity, while upregulated DEGs involved actin and mitogen-activated protein kinase signaling pathways. The correlation analysis of DEGs and the PPI network identified genes associated with FLNC. According to the immune infiltration analysis, the DCM group was more associated with immunity, and the infiltrating plasma cells had a strong correlation with the FLNC gene; we identified eight miRNAs and 29 lncRNAs that bind to the FLNC gene. The final gene sequencing results show that a total of eight FLNC-specific missense mutations were detected, among which FLNCT407N and FLNCR437L are rare mutations. Additionally, the mutation frequency and minimum allele frequencies determined by sequence comparison were higher than those of databases such as the 1,000Genomes database, and all were predicted to be harmful mutations by SIFT, PolyPhen-2, and Mutation Assessor software. FLNCR437L, FLNCT834M, FLNCG1264S, FLNCR1567Q, and FLNCL2538F mutations are highly conserved among different species and were verified as heterozygous mutations by Sanger sequencing, while FLNCV452M may be the pathogenic site of DCM. Conclusion: The data analysis of myocardial tissue samples and the mutation analysis of DCM serum samples provides a rich perspective for exploring the biological functions, molecular mechanisms, immune cell correlations, ceRNA networks, and pathogenic gene mutation sites connected to FLNC in DCM.

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Section: Discussionmentioning

confidence: 99%

Multiple effect mechanisms of FLNC in dilated cardiomyopathy based on genetic variants, transcriptomics, and immune infiltration analysis

Cai

et al. 2023

Preprint

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“…13 Non-negative matrix factorization (NMF) is a technique which has the great advantage of reducing a large number of variables into more easily interpreted latent factors shared across a large dataset. 14 NMF was first applied in facial recognition, 15,16 then subsequently in medicine for, for example, analyzing PET images; 17 cardiological diagnosis and risk assessment; 18,19 finding clusters of cancer subtypes; 20 and so on. It has not so far been used for an integrated analysis of QoL subtypes.…”

Section: Introductionmentioning

confidence: 99%

An machine learning model to predict quality of life subtypes of disabled stroke survivors

Xu,

Lei,

Lin

et al. 2023

Ann Clin Transl Neurol

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ObjectiveStroke causes serious physical disability with impaired quality of life (QoL) and heavy burden on health. The goal of this study is to explore the impaired QoL typologies and their predicting factors in physically disabled stroke survivors with machine learning approach.MethodsNon‐negative matrix factorization (NMF) was applied to clustering 308 physically disabled stroke survivors in rural China based on their responses on the short form 36 (SF‐36) assessment of quality of life. Principal component analysis (PCA) was conducted to differentiate the subtypes, and the Boruta algorithm was used to identify the variables relevant to the categorization of two subtypes. A gradient boosting machine(GBM) and local interpretable model‐agnostic explanation (LIME) algorithms were used to apply to interpret the variables that drove subtype predictions.ResultsTwo distinct subtypes emerged, characterized by short form 36 (SF‐36) domains. The feature difference between worsen QoL subtype and better QoL subtype was as follows: role‐emotion (RE), body pain (BP) and general health (GH), but not physical function (PF); the most relevant predictors of worsen QoL subtypes were help from others, followed by opportunities for community activity and rehabilitation needs, rather than disability severity or duration since stroke.InterpretationThe results suggest that the rehabilitation programs should be tailored toward their QoL clustering feature; body pain and emotional‐behavioral problems are more crucial than motor deficit; stroke survivors with worsen QoL subtype are most in need of social support, return to community, and rehabilitation.

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The rise of nonnegative matrix factorization: Algorithms and applications

Guo,

Li,

Liang

2024

Information Systems

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

Cited by 6 publications

References 63 publications

Multiple effect mechanisms of FLNC in dilated cardiomyopathy based on genetic variants, transcriptomics, and immune infiltration analysis

Multiple effect mechanisms of FLNC in dilated cardiomyopathy based on genetic variants, transcriptomics, and immune infiltration analysis

An machine learning model to predict quality of life subtypes of disabled stroke survivors

The rise of nonnegative matrix factorization: Algorithms and applications

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