Conduction defects in pediatric patients with Pearson syndrome: When to pace?

Shahid, Saneeha; Assaad, Iqbal El; Patel, Akash R.; Parikh, Sumit; Aziz, Peter F.

doi:10.1016/j.hrthm.2023.07.004

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…Other diseases from cluster 2 that are considered associated with lymphoma and leukaemia in the literature include ataxia telangiectasia [ 54 ], Bloom syndrome [ 55 ], cartilage-hair hypoplasia [ 56 ], and Chediak-Higashi syndrome [ 57 ], among others. Moreover, many diseases from cluster 2 could be associated with cardiovascular diseases, according to the literature: congenital heart defects are observed in 50-85% of cases of CHARGE syndromes [ 58 ]; the TARP syndrome is associated with congenital heart defects [ 59 ]; congenital heart disease is a common feature in the 22q11.2 deletion syndrome (DiGeorge syndrome) [ 60 ]; Parry Romberg syndrome is associated with hypertrophic cardiomyopathy and rheumatologic heart disease [ 61 ]; lichen sclerosus is associated with increased risk of cardiovascular comorbidities in female [ 62 ]; Pearson syndrome is often associated with cardiac conduction defects [ 63 ]; the association of inclusion body myositis and cardiac disease is debated [ 64 ]; a case of Melkersson-Rosenthal syndrome affecting cardiac connective tissues was reported in [ 65 ].…”

Section: Diffusion Profiles Comparison To Unveil Immune Diseases Simi...mentioning

confidence: 99%

Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond

Baptista,

Brière,

Baudot

2024

BMC Bioinformatics

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Background Biological networks have proven invaluable ability for representing biological knowledge. Multilayer networks, which gather different types of nodes and edges in multiplex, heterogeneous and bipartite networks, provide a natural way to integrate diverse and multi-scale data sources into a common framework. Recently, we developed MultiXrank, a Random Walk with Restart algorithm able to explore such multilayer networks. MultiXrank outputs scores reflecting the proximity between an initial set of seed node(s) and all the other nodes in the multilayer network. We illustrate here the versatility of bioinformatics tasks that can be performed using MultiXrank. Results We first show that MultiXrank can be used to prioritise genes and drugs of interest by exploring multilayer networks containing interactions between genes, drugs, and diseases. In a second study, we illustrate how MultiXrank scores can also be used in a supervised strategy to train a binary classifier to predict gene-disease associations. The classifier performance are validated using outdated and novel gene-disease association for training and evaluation, respectively. Finally, we show that MultiXrank scores can be used to compute diffusion profiles and use them as disease signatures. We computed the diffusion profiles of more than 100 immune diseases using a multilayer network that includes cell-type specific genomic information. The clustering of the immune disease diffusion profiles reveals shared shared phenotypic characteristics. Conclusion Overall, we illustrate here diverse applications of MultiXrank to showcase its versatility. We expect that this can lead to further and broader bioinformatics applications.

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Section: Diffusion Profiles Comparison To Unveil Immune Diseases Simi...mentioning

confidence: 99%

Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond

Baptista,

Brière,

Baudot

2024

BMC Bioinformatics

View full text Add to dashboard Cite

show abstract

“…Other diseases from cluster 2 that are considered associated with lymphoma and leukemia in the literature include ataxia telangiectasia [45], Bloom syndrome [46], cartilage-hair hypoplasia [47], and Chediak-Higashi syndrome [48], among others. Moreover, many diseases from cluster 2 could be associated with cardiovascular diseases, according to the literature: congenital heart defects are observed in 50–85% of cases of CHARGE syndromes [49] ; the TARP syndrome is associated with congenital heart defects [50] ; congenital heart disease is a common feature in the 22q11.2 deletion syndrome (DiGeorge syndrome) [51] ; Parry Romberg syndrome is associated with hypertrophic cardiomyopathy and rheumatologic heart disease [52] ; lichen sclerosus is associated with increased risk of cardiovascular comorbidities in female [53] ; Pearson syndrome is often associated with cardiac conduction defects [54] ; the association of inclusion body myositis and cardiac disease is debated [55] ; a case of Melkersson–Rosenthal syndrome affecting cardiac connective tissues was reported in [56].…”

Section: Diffusion Profiles Comparison To Unveil Immune Diseases Simi...mentioning

confidence: 99%

Random Walk with Restart on multilayer networks: from node prioritisation to supervised link prediction and beyond

Baptista,

Brière,

Baudot

2023

Preprint

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Background: Biological networks have proven invaluable ability for representing biological knowledge. Multilayer networks, which gather different types of nodes and edges in multiplex, heterogeneous and bipartite networks, provide a natural way to integrate diverse and multi-scale data sources into a common framework. Recently, we developed MultiXrank, a Random Walk with Restart algorithm able to explore such multilayer networks. MultiXrank outputs scores reflecting the proximity between an initial set of seed node(s) and all the other nodes in the multilayer network. We illustrate here the versatility of bioinformatics tasks that can be performed using MultiXrank. Results: We first show that MultiXrank can be used to prioritise genes and drugs of interest by exploring multilayer networks containing interactions between genes, drugs, and diseases. In a second study, we illustrate how MultiXrank scores can also be used in a supervised strategy to train a binary classifier to predict gene-disease associations. The classifier performance are validated using outdated and novel gene-disease association for training and evaluation, respectively. Finally, we show that MultiXrank scores can be used to compute diffusion profiles and use them as disease signatures. We computed the diffusion profiles of more than 100 immune diseases using a multilayer network that includes cell-type specific genomic information. The clustering of the immune disease diffusion profiles reveals shared shared phenotypic characteristics. Conclusion: Overall, we illustrate here diverse applications of MultiXrank to showcase its versatility. We expect that this can lead to further and broader bioinformatics applications.

show abstract

Conduction defects in pediatric patients with Pearson syndrome: When to pace?

Cited by 2 publications

References 2 publications

Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond

Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond

Random Walk with Restart on multilayer networks: from node prioritisation to supervised link prediction and beyond

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