kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Multi-omics approaches for revealing the complexity of cardiovascular disease
Kings Coll London, London, England..
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0003-2261-0881
Kings Coll London, London, England..ORCID iD: 0000-0002-4476-0971
Kings Coll London, London, England..ORCID iD: 0000-0001-5287-5026
Show others and affiliations
2021 (English)In: Briefings in Bioinformatics, ISSN 1467-5463, E-ISSN 1477-4054, Vol. 22, no 5, article id bbab061Article, review/survey (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Oxford University Press (OUP) , 2021. Vol. 22, no 5, article id bbab061
Keywords [en]
systems biology, cardiovascular disease, omics integration, integrated networks, genome-scale metabolic model
National Category
Cardiology and Cardiovascular Disease
Identifiers
URN: urn:nbn:se:kth:diva-305108DOI: 10.1093/bib/bbab061ISI: 000709461800093PubMedID: 33725119Scopus ID: 2-s2.0-85115631020OAI: oai:DiVA.org:kth-305108DiVA, id: diva2:1613428
Note

QC 20211122

Available from: 2021-11-22 Created: 2021-11-22 Last updated: 2025-02-10Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records

Arif, MuhammadUhlén, MathiasMardinoglu, Adil

Search in DiVA

By author/editor
Arif, MuhammadLam, SimonBayraktar, AbdulahadUhlén, MathiasMardinoglu, Adil
By organisation
Systems BiologyScience for Life Laboratory, SciLifeLab
In the same journal
Briefings in Bioinformatics
Cardiology and Cardiovascular Disease

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 162 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf