Overlapping Pathogenic Signalling Pathways and Biomarkers in Preeclampsia and Cardiovascular Disease
- Publisher:
- Elsevier
- Publication Type:
- Journal Article
- Citation:
- Pregnancy Hypertension, 2020, 20, pp. 131-136
- Issue Date:
- 2020-03-29
Closed Access
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1-s2.0-S2210778920300386-main.pdf | Published version | 1.33 MB | Adobe PDF |
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Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Suvakov, S | |
dc.contributor.author | Bonner, E | |
dc.contributor.author | Nikolic, V | |
dc.contributor.author | Jerotic, D | |
dc.contributor.author | Simic, TP | |
dc.contributor.author | Garovic, VD | |
dc.contributor.author | Lopez-Campos, G | |
dc.contributor.author |
McClements, L https://orcid.org/0000-0002-4911-1014 |
|
dc.date.accessioned | 2021-01-11T05:45:30Z | |
dc.date.available | 2020-03-27 | |
dc.date.available | 2021-01-11T05:45:30Z | |
dc.date.issued | 2020-03-29 | |
dc.identifier.citation | Pregnancy Hypertension, 2020, 20, pp. 131-136 | |
dc.identifier.issn | 2210-7789 | |
dc.identifier.issn | 2210-7797 | |
dc.identifier.uri | http://hdl.handle.net/10453/145298 | |
dc.description.abstract | Objectives Preeclampsia is a cardiovascular pregnancy complication which occurs in 5-10% of pregnancies that can lead to a number of pregnancy complications including maternal and foetal death. Long-term, preeclampsia is associated with up to 8-fold increased risk of cardiovascular disease (CVD) for both mothers and their offspring. The lack of mechanistic data in relation to the causes or consequences of preeclampsia has prevented the development of effective therapeutic or monitoring strategies. Study design This study investigates common underlying mechanisms of preeclampsia and CVD, specifically hypertension and heart failure with preserved ejection fraction (HFpEF) using “in silico” approach of publicly available datasets. Integrated techniques were designed to mine data repositories and identify relevant biomarkers associated with these three conditions. Main outcomes measures The knowledge base tools were employed that enabled the analysis of these biomarkers to discover potential molecular and biological links between these three conditions. Results Our bioinformatics “in silico” analyses of the publically available datasets identified 76 common biomarkers between preeclampsia, hypertension and HFpEF. These biomarkers were representative of 29 pathways commonly enriched across the three conditions which were largely related to inflammation, metabolism, angiogenesis, remodelling, haemostasis, apoptosis and the renin-angiotensin-aldosterone (RAAS) system. Conclusions This bioinformatics approach which uses the wealth of scientific data available in public repositories can be helpful to gain a deeper understanding of the overlapping pathogenic mechanisms of associated diseases, which could be explored as biomarkers or targets to prevent long-term cardiovascular complications such as hypertension and HFpEF following preeclampsia. | |
dc.format | Print-Electronic | |
dc.language | eng | |
dc.publisher | Elsevier | |
dc.relation.ispartof | Pregnancy Hypertension | |
dc.relation.isbasedon | 10.1016/j.preghy.2020.03.011 | |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.subject | 1114 Paediatrics and Reproductive Medicine | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Pre-Eclampsia | |
dc.subject.mesh | Hypertension | |
dc.subject.mesh | Stroke Volume | |
dc.subject.mesh | Computational Biology | |
dc.subject.mesh | Signal Transduction | |
dc.subject.mesh | Pregnancy | |
dc.subject.mesh | Blood Pressure | |
dc.subject.mesh | Ventricular Function, Left | |
dc.subject.mesh | Databases, Genetic | |
dc.subject.mesh | Female | |
dc.subject.mesh | Gene Regulatory Networks | |
dc.subject.mesh | Heart Failure | |
dc.subject.mesh | Blood Pressure | |
dc.subject.mesh | Computational Biology | |
dc.subject.mesh | Databases, Genetic | |
dc.subject.mesh | Female | |
dc.subject.mesh | Gene Regulatory Networks | |
dc.subject.mesh | Heart Failure | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Hypertension | |
dc.subject.mesh | Pre-Eclampsia | |
dc.subject.mesh | Pregnancy | |
dc.subject.mesh | Signal Transduction | |
dc.subject.mesh | Stroke Volume | |
dc.subject.mesh | Ventricular Function, Left | |
dc.title | Overlapping Pathogenic Signalling Pathways and Biomarkers in Preeclampsia and Cardiovascular Disease | |
dc.type | Journal Article | |
utslib.citation.volume | 20 | |
utslib.location.activity | Netherlands | |
utslib.for | 1114 Paediatrics and Reproductive Medicine | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Science | |
pubs.organisational-group | /University of Technology Sydney/Strength - IBMD - Initiative for Biomedical Devices | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Science/School of Life Sciences | |
pubs.organisational-group | /University of Technology Sydney | |
utslib.copyright.status | closed_access | * |
pubs.consider-herdc | true | |
dc.date.updated | 2021-01-11T05:44:55Z | |
pubs.publication-status | Published online | |
pubs.volume | 20 |
Abstract:
Objectives
Preeclampsia is a cardiovascular pregnancy complication which occurs in 5-10% of pregnancies that can lead to a number of pregnancy complications including maternal and foetal death. Long-term, preeclampsia is associated with up to 8-fold increased risk of cardiovascular disease (CVD) for both mothers and their offspring. The lack of mechanistic data in relation to the causes or consequences of preeclampsia has prevented the development of effective therapeutic or monitoring strategies.
Study design
This study investigates common underlying mechanisms of preeclampsia and CVD, specifically hypertension and heart failure with preserved ejection fraction (HFpEF) using “in silico” approach of publicly available datasets. Integrated techniques were designed to mine data repositories and identify relevant biomarkers associated with these three conditions.
Main outcomes measures
The knowledge base tools were employed that enabled the analysis of these biomarkers to discover potential molecular and biological links between these three conditions.
Results
Our bioinformatics “in silico” analyses of the publically available datasets identified 76 common biomarkers between preeclampsia, hypertension and HFpEF. These biomarkers were representative of 29 pathways commonly enriched across the three conditions which were largely related to inflammation, metabolism, angiogenesis, remodelling, haemostasis, apoptosis and the renin-angiotensin-aldosterone (RAAS) system.
Conclusions
This bioinformatics approach which uses the wealth of scientific data available in public repositories can be helpful to gain a deeper understanding of the overlapping pathogenic mechanisms of associated diseases, which could be explored as biomarkers or targets to prevent long-term cardiovascular complications such as hypertension and HFpEF following preeclampsia.
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