The role of inflammation in vascular function and pregnancy outcome in the pregnant stroke prone spontaneously hypertensive rat

During pregnancy, the maternal cardiovascular system undergoes major adaptation. One of these changes is a 40-50 % increase in circulating blood volume which requires a systemic remodelling of the vasculature in order to regulate maternal blood pressure and maximise blood supply to the developing placenta and fetus. These changes are broadly conserved between humans and rats making them an appropriate pre-clinical model in which to study the underlying mechanisms of pregnancy-dependent cardiovascular remodelling. Whilst women are normally protected against cardiovascular disease; pregnancy marks a period of time where women are susceptible to cardiovascular complications. Cardiovascular disease is the leading cause of maternal mortality in the United Kingdom; in particular hypertensive conditions are among the most common complications of pregnancy. One of the main underlying pathologies of these pregnancy complications is thought to be a failure of the maternal cardiovascular system to adapt. The remodelling of the uterine arteries, which directly supply the maternal-fetal interface, is paramount to a healthy pregnancy. Failure of the uterine arteries to remodel sufficiently can result in a number of obstetric complications such as preeclampsia, fetal growth restriction and spontaneous pregnancy loss. At present, it is poorly understood whether this deficient vascular response is due to a predisposition from existing maternal cardiovascular risk factors, the physiological changes that occur during pregnancy or a combination of both. Previous work in our group employed the stroke prone spontaneously hypertensive rat (SHRSP) as a model to investigate pregnancy-dependent remodelling of the uterine arteries. The SHRSP develops hypertension from 6 weeks of age and can be contrasted with the control strain, the Wistar Kyoto (WKY) rat. The phenotype of the SHRSP is therefore reflective of the clinical situation of maternal chronic hypertension during pregnancy. We showed that the SHRSP exhibited a deficient uterine artery remodelling response with respect to both structure and function accompanied by a reduction in litter size relative to the WKY at gestational day (GD) 18. A previous intervention study using nifedipine in the SHRSP achieved successful blood pressure reduction from 6 weeks of age and throughout pregnancy; however uterine artery remodelling and litter size at GD18 was not improved. We concluded that the abnormal uterine artery remodelling present in the SHRSP was independent of chronic hypertension. From these findings, we hypothesised that the SHRSP could be a novel model of spontaneously deficient uterine artery remodelling in response to pregnancy which was underpinned by other as yet unidentified cardiovascular risk factors. In Chapter 1 of this thesis, I have characterised the maternal, placental and fetal phenotype in pregnant (GD18) SHRSP and WKY. The pregnant SHRSP exhibit features of left ventricular hypertrophy in response to pregnancy and altered expression of maternal plasma biomarkers which have been previously associated with hypertension in human pregnancy. I developed a protocol for accurate dissection of the rat uteroplacental unit using qPCR probes specific for each layer. This allowed me to make an accurate and specific statement about gene expression in the SHRSP GD18 placenta; where oxidative stress related gene markers were increased in the vascular compartments. The majority of SHRSP placenta presented at GD18 with a blackened ring which encircled the tissue. Further investigation of the placenta using western blot for caspase 3 cleavage determined that this was likely due to increased cell death in the SHRSP placenta. The SHRSP also presented with a loss of one particular placental cell type at GD18: the glycogen cells. These cells could have been the target of cell death in the SHRSP placenta or were utilised early in pregnancy as a source of energy due to the deficient uterine artery blood supply. Blastocyst implantation was not altered but resorption rate was increased between SHRSP and WKY; indicating that the reduction in litter size in the SHRSP was primarily due to late (>GD14) pregnancy loss. Fetal growth was not restricted in SHRSP which led to the conclusion that SHRSP sacrifice part of their litter to deliver a smaller number of healthier pups. Activation of the immune system is a common pathway that has been implicated in the development of both hypertension and adverse pregnancy outcome. In Chapter 2, I proposed that this may be a mechanism of interest in SHRSP pregnancy and measured the pro-inflammatory cytokine, TNFα, as a marker of inflammation in pregnant SHRSP and WKY and in the placentas from these animals. TNFα was up-regulated in maternal plasma and urine from the GD18 SHRSP. In addition, TNFα release was increased from the GD18 SHRSP placenta as was the expression of the pro-inflammatory TNFα receptor 1 (Tnfr1). In order to investigate whether this excess TNFα was detrimental to SHRSP pregnancy, a vehicle-controlled intervention study using etanercept (a monoclonal antibody which works as a TNFα antagonist) was carried out. Etanercept treatment at GD0, 6, 12 and 18 resulted in an improvement in pregnancy outcome in the SHRSP with an increased litter size and reduced resorption rate. Furthermore, there was an improved uterine artery function in GD18 SHRSP treated with etanercept which was associated with an improved uterine artery blood flow over the course of gestation. In Chapter 3, I sought to identify the source of this detrimental excess of TNFα by designing a panel for maternal leukocytes in the blood and placenta at GD18. A population of CD3- CD161+ cells, which are defined as rat natural killer (NK) cells, were increased in number in the SHRSP. Intracellular flow cytometry also identified this cell type as a source of excess TNFα in blood and placenta from pregnant SHRSP. I then went on to evaluate the effects of etanercept treatment on these CD3- CD161+ cells and showed that etanercept reduced the expression of CD161 and the cytotoxic molecule, granzyme B, in the NK cells. Thus, etanercept limits the cytotoxicity and potential damaging effect of these NK cells in the SHRSP placenta. Analysing the urinary peptidome has clinical potential to identify novel pathways involved with disease and/or to develop biomarker panels to aid and stratify diagnosis. In Chapter 4, I utilised the SHRSP as a pre-clinical model to identify novel urinary peptides associated with hypertensive pregnancy. Firstly, a characterisation study was carried out in the kidney of the WKY and SHRSP. Urine samples from WKY and SHRSP taken at pre-pregnancy, mid-pregnancy (GD12) and late pregnancy (GD18) were used in the peptidomic screen. In order to capture peptides which were markers of hypertensive pregnancy from the urinary peptidomic data, I focussed on those that were only changed in a strain dependent manner at GD12 and 18 and not pre-pregnancy. Peptide fragments from the uromodulin protein were identified from this analysis to be increased in pregnant SHRSP relative to pregnant WKY. This increase in uromodulin was validated at the SHRSP kidney level using qPCR. Uromodulin has previously been identified to be a candidate molecule involved in systemic arterial hypertension but not in hypertensive pregnancy thus is a promising target for further study. In summary, we have characterised the SHRSP as the first model of maternal chronic hypertension during pregnancy and identified that inflammation mediated by TNFα and NK cells plays a key role in the pathology. The evidence presented in this thesis establishes the SHRSP as a pre-clinical model for pregnancy research and can be continued into clinical studies in pregnant women with chronic hypertension which remains an area of unmet research need.

Exploring the potential role of allostatic load biomarkers in risk assessment of patients presenting with depressive symptoms

Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation.