Integrative transcriptomic analysis of tissue-specific metabolic crosstalk after myocardial infarction

Arif, Muhammad; Klevstig, Martina; Benfeitas, Rui; Doran, Stephen; Türkez, Hasan; Uhlén, Mathias; Clausen, Maryam; Wikström, Johannes; Etal, Damla; Zhang, Cheng; Levin, Malin; Mardinoğlu, Adil; Borén, Jan

doi:10.1101/2020.10.28.358556

Cited by 5 publications

(6 citation statements)

References 57 publications

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“…There is also the need to further understand tissue-specific metabolic crosstalk through integration of models of the heart and other human tissues with the gut microbiota for the simulation of whole-body metabolic functions in health and CVD, with such roadmaps having already been designed for the study of liver-associated diseases [ 206 ]. This multi-tissue approach has been limited to date for CVD [ 207 ] and future efforts should focus on the generation of a final predictive model incorporating essential metabolic interactions or signalling pathways in each individual tissue/microbiota model that are known to either protect against or contribute towards the development and progression of CVD.…”

Section: Discussionmentioning

confidence: 99%

Multi-omics approaches for revealing the complexity of cardiovascular disease

Doran

Arif

Lam

et al. 2021

Briefings in Bioinformatics

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The development and progression of cardiovascular disease (CVD) can mainly be attributed to the narrowing of blood vessels caused by atherosclerosis and thrombosis, which induces organ damage that will result in end-organ dysfunction characterized by events such as myocardial infarction or stroke. It is also essential to consider other contributory factors to CVD, including cardiac remodelling caused by cardiomyopathies and co-morbidities with other diseases such as chronic kidney disease. Besides, there is a growing amount of evidence linking the gut microbiota to CVD through several metabolic pathways. Hence, it is of utmost importance to decipher the underlying molecular mechanisms associated with these disease states to elucidate the development and progression of CVD. A wide array of systems biology approaches incorporating multi-omics data have emerged as an invaluable tool in establishing alterations in specific cell types and identifying modifications in signalling events that promote disease development. Here, we review recent studies that apply multi-omics approaches to further understand the underlying causes of CVD and provide possible treatment strategies by identifying novel drug targets and biomarkers. We also discuss very recent advances in gut microbiota research with an emphasis on how diet and microbial composition can impact the development of CVD. Finally, we present various biological network analyses and other independent studies that have been employed for providing mechanistic explanation and developing treatment strategies for end-stage CVD, namely myocardial infarction and stroke.

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Section: Discussionmentioning

confidence: 99%

Multi-omics approaches for revealing the complexity of cardiovascular disease

Doran

Arif

Lam

et al. 2021

Briefings in Bioinformatics

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“…In another case study, a cardiomyocyte-specific GEM, iCardio, was reconstructed to explore whether the metabolic profile of all heart failure is similar (111). Arif et al (112) used transcriptomic data to reconstruct a cell-specific GEM and investigated metabolic alterations that emerged after myocardial infarction. They reported a set of gene clusters associated with myocardial infarction in the heart and liver.…”

Section: Box Integration Of Omics With a Gemmentioning

confidence: 99%

Emerging computational paradigms to address the complex role of gut microbial metabolism in cardiovascular diseases

Aminian-Dehkordi

Valiei

Mofrad

2022

Front. Cardiovasc. Med.

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The human gut microbiota and its associated perturbations are implicated in a variety of cardiovascular diseases (CVDs). There is evidence that the structure and metabolic composition of the gut microbiome and some of its metabolites have mechanistic associations with several CVDs. Nevertheless, there is a need to unravel metabolic behavior and underlying mechanisms of microbiome-host interactions. This need is even more highlighted when considering that microbiome-secreted metabolites contributing to CVDs are the subject of intensive research to develop new prevention and therapeutic techniques. In addition to the application of high-throughput data used in microbiome-related studies, advanced computational tools enable us to integrate omics into different mathematical models, including constraint-based models, dynamic models, agent-based models, and machine learning tools, to build a holistic picture of metabolic pathological mechanisms. In this article, we aim to review and introduce state-of-the-art mathematical models and computational approaches addressing the link between the microbiome and CVDs.

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“…These subnetworks are usually referred to as communities or clusters. Community detections assisted researchers in getting hidden insights into biological networks, such as in the multi-tissue gene co-expression networks of heart disease (23) or integrated networks in NAFLD (24).…”

Section: Key Bacterial Family Differs Between Healthy and T2d Networkmentioning

confidence: 99%

GutMicroNet: an interactive platform for gut microbiome interaction exploration

Arif

Portlock

Güngör³

et al. 2021

Preprint

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The human gut microbiome data has been proven to be a powerful tool to understand the human body in both health and disease conditions. However, understanding their complex interactions and impact on the human body remains a challenging task. Unravelling the species-level interactions could allow us to study the causality of the microbiome. Moreover, it could lead us to better understand the underlying mechanisms of complex diseases and, subsequently, the discovery of new therapeutic targets. Given these challenges and benefits, it has become evident that a freely accessible and centralized platform for presenting gut microbiome interaction is essential to untangle the complexity and open multiple new paths and opportunities in disease- and drug-related research. Here, we present GutMicroNet, an interactive visualization platform of human gut microbiome interaction networks. We generated 45 gut microbiome co-abundance networks from various geographical origins, gender, and diseases based on the data presented in the Human Gut Microbiome Atlas. This interactive platform includes more than 1900 gut microbiome species and allows users to query multiple species at the same time based on their interests and adjust it based on the statistical properties. Moreover, users can download publication-ready figures or network information for further analysis. The platform can be accessed freely on https://gutmicro.net without any login requirements or limitations, including access to the full networks data.

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Integrative transcriptomic analysis of tissue-specific metabolic crosstalk after myocardial infarction

Cited by 5 publications

References 57 publications

Multi-omics approaches for revealing the complexity of cardiovascular disease

Multi-omics approaches for revealing the complexity of cardiovascular disease

Emerging computational paradigms to address the complex role of gut microbial metabolism in cardiovascular diseases

GutMicroNet: an interactive platform for gut microbiome interaction exploration

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