Acute phase proteins and biomarkers for health in chickens

Acute phase proteins (APPs) are proteins synthesised predominantly in the liver, whose plasma concentrations increase (positive APP) or decrease (negative APP) as a result of infection, inflammation, trauma and tissue injury. They also change as a result of the introduction of immunogens such as bacterial lipopolysaccharide (LPS), turpentine and vaccination. While publications on APPs in chickens are numerous, the limited availability of anti-sera and commercial ELISAs has resulted in a lot of information on only a few APPs. Disease is a threat to the poultry industry, as pathogens have the potential to evolve, spread and cause rapid onset of disease that is detrimental to the welfare of birds. Low level, sub-acute disease with non-specific, often undiagnosed causes can greatly affect bird health and growth and impact greatly on productivity and profitability. Developing and validating methods to measure and characterise APPs in chickens will allow these proteins to be used diagnostically for monitoring flock health. Using immune parameters such as APPs that correlate with disease resistance or improvements in production and welfare will allow the use of APPs as selection parameters for breeding to be evaluated. For APPs to be useful parameters on which to evaluate chicken health, information on normal APP concentrations is required. Ceruloplasmin (Cp) and PIT54 concentrations were found to be much lower in healthy birds form commercial production farms than the reported normal values obtained from the literature. These APPs were found to be significantly higher in culled birds from a commercial farm and Cp, PIT54 and ovotransferrin (Ovt) were significantly higher in birds classified as having obvious gait defects. Using quantitative shotgun proteomics to identify the differentially abundant proteins between three pools: highly acute phase (HAP), acute phase (AP) and non-acute phase (NAP), generated data from which a selection of proteins, based on the fold difference between the three pools was made. These proteins were targeted on a individual samples alongside proteins known to be APPs in chickens or other species: serum amyloid A (SAA), C-reactive protein (CRP), Ovt, apolipoprotein A-I (apo-AI), transthyretin (Ttn), haemopexin (Hpx) and PIT54. Together with immunoassay data for SAA, Ovt, alpha-1-acid glycoprotein (AGP) and Cp the results of this research reveal that SAA is the only major APP in chickens. Ovotransferrin and AGP behave as moderate APPs while PIT54 and Cp are minor APPs. Haemopexin was not significantly different between the three acute phase groups. Apolipoprotein AI and Ttn were significantly lower in the HAP and AP groups and as such can be classed as negative APPs. In an effort to identify CRP, multiple anti-sera cross reacting with CRP from other species were used and a phosphorylcholine column known to affinity purify CRP were used. Enriched fractions containing low molecular weight proteins, elutions from the affinity column together with HAP, AP and NAP pooled samples were applied to a Q-Exactive Hybrid Quadrupole–Orbitrap mass spectrometer (Thermo Scientific) for Shotgun analysis and CRP was not identified. It would appear that CRP is not present as a plasma protein constitutively or during an APR in chickens and as such is not an APP in this species. Of the proteins targeted as possible novel biomarkers of the APR in chickens mannan binding lectin associated serine protease-2, α-2-HS-glycoprotein (fetuin) and major facilitator superfamily domain-containing protein 10 were reduced in abundance in the HAP group, behaving as negative biomarkers. Myeloid protein and putative ISG(12)2 were positively associated with the acute phase being significantly higher in the HAP and AP groups. The protein cathepsin D was significantly higher in both HAP and AP compared to the NAP indicating that of all the proteins targeted, this appears to have the most potential as a biomarker of the acute phase, as it was significantly increased in the AP as well as the HAP group. To evaluate APPs and investigate biomarkers of intestinal health, a study using re-used poultry litter was undertaken. The introduction of litter at 12 days of age did not significantly increase any APPs measured using immunoassays and quantitative proteomics at 3, 6 and 10 days post introduction. While no APP was found to be significantly different between the challenged and control groups at anytime point, the APPs AGP, SAA and Hpx did increase over time in all birds. The protein apolipoprotein AIV (apo-AIV) was targeted as a possible APP and because of its reported role in controlling satiety. An ELISA was developed, successfully validated and used to measure apo-AIV in this study. While no significant differences in apo-AIV plasma concentrations between challenged and control groups were identified apo-AIV plasma concentrations did change significantly between certain time points in challenged and control groups. Apoliporotein AIV does not appear to behave as an APP in chickens, as it was not significantly different between acute phase groups. The actin associated proteins villin and gelsolin were investigated as possible biomarkers of intestinal health. Villin was found not to be present in the plasma of chickens and as such not a biomarker target. Gelsolin was found not to be differentially expressed during the acute phase or as a result of intestinal challenge. Finally a proteomic approach was undertaken to investigate gastrocnemius tendon (GT) rupture in broiler chickens with a view of elucidating to and identify proteins associated with risk of rupture. A number of proteins were found to be differentially expressed between tendon pools and further work would enable further detailing of these findings. In conclusion this work has made a number of novel findings and addressed a number of data poor areas. The area of chicken APPs research has stagnated over the last 15 years with publications becoming repetitive and reliant on a small number of immunoassays. This work has sought to characterise the classic APPs in chickens, and use a quantitative proteomic approach to measure and categorise them. This method was also used to take a fresh approach to biomarker identification for both the APR and intestinal health. The development and validation of assays for Ovt and apo-AIV and the shotgun data mean that these proteins can be further characterised in chickens with a view of applying their measurement to diagnostics and selective breeding programs.

An investigation of the clinical utility of preoperative cardiopulmonary exercise testing in patients undergoing major pancreatic surgery

Pancreaticoduodenectomy with or without adjuvant chemotherapy remains the only modality of possible cure in patients with cancer involving the head of the pancreas and the periampullary region. While mortality rates after pancreaticoduodenectomy have improved considerably over the course of the last century, morbidity remains high. Patient selection is of paramount importance in ensuring that major surgery is offered to individuals who will most benefit from a pancreaticoduodenectomy. Moreover, identifying preoperative risk factors provides potential targets for prehabilitation and optimisation of the patient's physiology before undertaking surgery. In addition to this, early identification of patients who are likely to develop postoperative complications allows for better allocation of critical care resources and more aggressive management high risk patients. Cardiopulmonary exercise testing is becoming an increasingly popular tool in the preoperative risk assessment of the surgical patient. However, very little work has been done to investigate the role of cardiopulmonary exercise testing in predicting complications after pancreaticoduodenectomy. The impact of jaundice, systemic inflammation and other preoperative clinicopathological characteristics on cardiopulmonary exercise physiology has not been studied in detail before in this cohort of patients. The overall aim of the thesis was to examine the relationships between preoperative clinico-pathological characteristics including cardiopulmonary exercise physiology, obstructive jaundice, body composition and systemic inflammation and complications and the post-surgical systemic inflammatory response in patients undergoing pancreaticoduodenectomy. Chapter 1 reviews the existing literature on preoperative cardiopulmonary exercise testing, the impact of obstructive jaundice, perioperative systemic inflammation and the importance of body composition in determining outcomes in patients undergoing major surgery with particular reference to pancreatic surgery. Chapter 2 reports on the role of cardiopulmonary exercise testing in predicting postoperative complications after pancreaticoduodenectomy. The results demonstrate that patients with V˙O2AT less than 10 ml/kg/min are more likely to develop a postoperative pancreatic fistula, stay longer in hospital and less likely to receive adjuvant therapy. These results emphasise the importance of aerobic fitness to recover from the operative stress of major surgery without significant morbidity. Cardiopulmonary exercise testing may prove useful in selecting patients for intensive prehabilitation programmes as well as for other optimisation measures to prepare them for major surgery. Chapter 3 evaluates the relationship between cardiopulmonary exercise physiology and other clinicopathological characteristics of the patient. A detailed analysis of cardiopulmonary exercise test parameters in jaundiced versus non-jaundiced patients demonstrates that obstructive jaundice does not impair cardiopulmonary exercise physiology. This further supports emerging evidence in contemporary literature that jaundiced patients can proceed directly to surgery without preoperative biliary drainage. The results of this study also show an interesting inverse relationship between body mass index and anaerobic threshold which is analysed in more detail in Chapter 4. Chapter 4 examines the relationship between preoperative cardiopulmonary exercise physiology and body composition in depth. All parameters measured at cardiopulmonary exercise test are compared against body composition and body mass index. The results of this chapter report that the current method of reporting V˙O2, both at peak exercise and anaerobic threshold, is biased against obese subjects and advises caution in the interpretation of cardiopulmonary exercise test results in patients with a high BMI. This is particularly important as current evidence in literature suggests that postoperative outcomes in obese subjects are comparable to non-obese subjects while cardiopulmonary exercise test results are also abnormally low in this very same cohort of patients. Chapter 5 analyses the relationship between preoperative clinico-pathological characteristics including systemic inflammation and the magnitude of the postoperative systemic inflammatory response. Obstructive jaundice appears to have an immunosuppressive effect while elevated preoperative CRP and hypoalbuminemia appear to have opposite effects with hypoalbuminemia resulting in a lower response while elevated CRP in the absence of hypoalbuminemia resulted in a greater postoperative systemic inflammatory response. Chapter 6 evaluates the role of the early postoperative systemic inflammatory response in predicting complications after pancreaticoduodenectomy and aims to establish clinically relevant thresholds for C-Reactive Protein for the prediction of complications. The results of this chapter demonstrate that CRP levels as early as the second postoperative day are associated with complications. While post-operative CRP was useful in the prediction of infective complications, this was the case only in patients who did not develop a post-operative pancreatic fistula. The predictive ability of inflammatory markers for infectious complications was blunted in patients with a pancreatic fistula. Chapter 7 summarises the findings of this thesis, their place in current literature and future directions. The results of this thesis add to the current knowledge regarding the complex pathophysiological abnormalities in patients undergoing pancreaticoduodenectomy, with specific emphasis on the interaction between cardiopulmonary exercise physiology, obstructive jaundice, systemic inflammation and postoperative outcomes. The work presented in this thesis lays the foundations for further studies aimed at improving outcomes after pancreaticoduodenectomy through the development of individualised, goal-directed therapies that are initiated well before this morbid yet necessary operation is performed.

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.