A stochastic model for early placental development.

Simon L Cotter, Václav Klika, Laura Kimpton, Sally Collins, Alexander E P Heazell

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

In the human, placental structure is closely related to placental function and consequent pregnancy outcome. Studies have noted abnormal placental shape in small-for-gestational-age infants which extends to increased lifetime risk of cardiovascular disease. The origins and determinants of placental shape are incompletely understood and are difficult to study in vivo. In this paper, we model the early development of the human placenta, based on the hypothesis that this is driven by a chemoattractant effect emanating from proximal spiral arteries in the decidua. We derive and explore a two-dimensional stochastic model, and investigate the effects of loss of spiral arteries in regions near to the cord insertion on the shape of the placenta. This model demonstrates that disruption of spiral arteries can exert profound effects on placental shape, particularly if this is close to the cord insertion. Thus, placental shape reflects the underlying maternal vascular bed. Abnormal placental shape may reflect an abnormal uterine environment, predisposing to pregnancy complications. Through statistical analysis of model placentas, we are able to characterize the probability that a given placenta grew in a disrupted environment, and even able to distinguish between different disruptions.
Original languageEnglish (US)
Pages (from-to)20140149
JournalJournal of the Royal Society Interface
Volume11
Issue number97
DOIs
StatePublished - May 21 2014
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-C1-013-04
Acknowledgements: The Study Group and a subsequent follow-up meeting were supported by the Engineering and Physical Sciences Research Council (EP/H00162X/1), and hosted by OCCAM, Mathematical Institute, University of Oxford, UK, with institutional support RVO:68407700 for V. K. This publication is based on work supported in part by award no. KUK-C1-013-04, made by King Abdullah University of Science and Technology (KAUST).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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