Comprehensive data analysis to study parturition
Sharp, Gemma Carly
Our limited understanding of the molecular mechanisms driving the onset of normal human parturition makes it difficult to identify ‘what goes wrong’ in conditions such as preterm labour (PTL), preterm prelabour rupture of membranes (PPROM) and postpartum haemorrhage (PPH). This incomplete understanding seriously hampers the development of effective ways to predict, prevent and treat parturition complications, which are a cause of significant neonatal and maternal morbidity. Two principal barriers to improving our understanding are 1) the great complexity of both the molecular interactions initiating parturition and the aetiology of parturition complications, and 2) the difficulty in generating relevant high quality molecular and epidemiological data. To help make sense of this complexity, data should be analysed comprehensively to maximise the amount of useful information gleaned from it. This thesis aimed to explore the use of specialist methods to analyse novel and previously published data to study the molecular mechanisms initiating human parturition and the epidemiology of parturition complications. The molecular mechanisms initiating parturition were explored through a gene expression microarray of labouring and non-labouring myometrial tissue. This is the largest microarray of its kind to date. Functional analysis and a network graph approach were used to reveal genes and molecular pathways associated with labour. The first ever meta-analysis of similar myometrial microarray datasets was also conducted to assess the reliability and generalisability of the results. This work supported the hypothesis that labour is associated with inflammatory events in the myometrium. A computer model of an inflammatory signalling pathway associated with infection-induced PTL was then built to provide proof of concept that such models can be used to study parturition. The model was based on published data and described lipopolysaccharide-induced activation of the transcription factor Nuclear Factor kappa B (NF-κB). This is the first attempt to generate a dynamic kinetic model that has relevance to the molecular mechanisms of PTL, and the first model of this pathway to explicitly include molecular interactions upstream of NF-κB activation. The epidemiology of complications at parturition was explored using three methods. Firstly, a novel approach was developed to use network graphs to visualise and analyse a dataset of nearly 50,000 birth records. The approach provided a quick and effective way to preliminarily explore relationships between exposures and pregnancy outcomes in an unbiased data-driven manner. Secondly, a record-linkage study of two datasets of birth records was conducted to determine risk factors for PPH, including intergenerational transmission of risk. This confirmed several known risk factors of PPH and showed that women whose mothers or grandmothers had PPH do not appear to be at increased risk themselves. Finally, a systematic review and meta-analysis of three randomised controlled trials investigated the effectiveness of fetal assessment methods in improving maternal and neonatal outcomes following PPROM. The review concluded that there is currently insufficient evidence on the benefits and harms of any method of fetal assessment, and further randomised controlled trials are required.