| Summary: | Cardiovascular disease is the leading cause of morbidity and mortality in the Western world, mainly through cerebrovascular and coronary artery related events. Cardiovascular disease is a chronic progressive disease with different stages. These stages can be assessed by a variety of biomarkers. Biomarker quantification can be used for different purposes: screening, prediction of disease recurrence, therapeutic monitoring, diagnosis and prognostication. Noninvasive, inexpensive diagnostic tests currently applied in clinical practice have a relative high rate of false positive and false negative results. Therefore further refinement of the diagnostic process could improve clinical care. Regarding prognostication the need for improvement also remains as current risk models only predict a small quantity of occurring cardiovascular events. The concept of the cardiovascular continuum postulates that cardiovascular disease consists of a chain of events, is initiated by numerous cardiovascular risk factors and subsequently progresses through pathophysiological processes, ultimately leading to end-stage heart failure. For that reason cardiovascular diseases are chronic progressive conditions and can be divided into different stages, such as early tissue dysfunction or subclinical atherosclerosis prior to development of clinically overt disease. Biomarkers suitable for prognostication and diagnosis can differ at each stage. The general aim of this thesis was therefore the investigation of a variety of biomarkers in diagnosis and prediction of cardiovascular disease at different stages of the cardiovascular continuum, as covered by three different study cohorts contributing to this thesis. This included several approaches: the comparison of central and peripheral pulse pressure in middle aged hypertensive patients in regards of their prognostic potential; the application of established circulating, functional and structural biomarkers to the diagnostic process of coronary artery disease in stable angina patients; the development/refinement of a urinary proteomic biomarker for coronary artery disease and the examination of its diagnostic potential in stable angina patients. Biomarkers successful in the diagnosis of coronary artery disease were included in multiple biomarker models. Aside from biomarker development for the general population, investigations of specific cohorts, such as patients with certain diseases and belonging to certain age groups or sharing specific biochemical features provided advances in the past. To estimate the potential of a biomarker in risk prediction association studies with surrogate biomarkers are applicable. We collected a cohort of middle-aged hypertensive patients to assess if central pulse pressure, derived from non-invasive assessment of arterial stiffness, could improve risk prediction. Central pulse pressure has been previously shown to have prognostic value in populations with end-stage renal failure, coronary artery disease and high prevalence of diabetes mellitus. Considering the prognostic information of peripheral pulse pressure in the elderly, the hypothesis that central pulse pressure could improve risk prediction is comprehensive and was investigated as part of this thesis. This was accomplished by comparing the strength of correlation between central or peripheral pulse pressure and these surrogate biomarkers. When compared to peripheral pulse pressure, central pulse pressure had stronger associations with aortic pulse wave velocity, carotid intima-media thickness, and left ventricular mass index, but equal association with the albumin:creatinine ratio. In contrast, after adjustment for age, mean arterial pressure, heart rate and hypertension status there was no significant difference between central and peripheral pulse pressure for prediction of listed surrogate biomarkers in multivariate analysis. These results suggested that central pulse pressure is unlikely to provide more prognostic information than peripheral pulse pressure in middle-aged hypertensive patients. The diagnosis of coronary artery disease is clinically relevant in symptomatic patients, either acute or stable. The diagnosis of stable flow limiting coronary artery disease is especially challenging as non-cardiac as well as other cardiac conditions can mimic symptoms. Non-invasive diagnostic tools have either moderate sensitivities or specificities, or are not widely available. Therefore new biomarkers for the diagnosis of flow limiting coronary artery disease have the potential to improve current diagnostic strategies. This could be accomplished adjacent to existing biomarkers or by replacement of such, due to cost effectiveness, better discriminatory etc. As part of this thesis, a biomarker identification and validation study was conducted into urinary proteomics of coronary artery disease. First we tried to replicate a study conducted by our research group in the past. Therein, an established coronary artery disease specific polypeptide pattern was unable to differentiate between patients with severe coronary artery disease and healthy controls despite strong cohort similarities to the original study. We therefore recalibrated the urinary polypeptide pattern using an enlarged biomarker discovery cohort and adjusted the pattern for lipid lowering and angiotensin converting enzyme inhibitor treatment effects. We calculated a score from the resulting polypeptide pattern, which identified coronary artery disease patients with a sensitivity of 79% and a specificity of 88% in a biomarker validation cohort. As the next step of biomarker development we performed a diagnostic validation study. The investigated clinical cohort consisted of stable angina patients with or without coronary artery disease. The new polypeptide pattern score was unable to differentiate between these two groups. The score however correlated strongly with coronary artery disease extent as measured by the Gensini score, implying that urinary proteomics in the diagnosis of coronary artery disease is promising, yet requires further effort before clinical employment. In addition to the urinary proteomic biomarker development second diagnostic approach was selected. As coronary artery disease is a complex chronic disease, the combination of different biomarkers should result in a better discrimination between stable angina patients with or without coronary artery disease. This approach attempts to position the individual as precisely as possible on the cardiovascular continuum including serologic, functional vascular and imaging biomarkers of subclinical atherosclerosis. Serologic markers thereby present a plasma proteomic approach covering pathophysiological processes with known correlation or causative for coronary artery disease. Functional and structural changes of the peripheral vasculature resemble the coronary artery system. We investigated circulating biomarkers and vascular biomarkers separately. A variety of circulating biomarkers differentiated patients with severe coronary artery disease from healthy control subjects. When patients with stable angina and with or without coronary artery disease as diagnosed by coronary angiography were investigated no statistically significant differences could be detected for circulating biomarkers. In the same study a microvascular biomarker, the reactive hyperaemia index, and a macrovascular biomarker, the carotide plaque score, were able to differentiated between cases and controls. Both markers either added separately or together improved the risk classification of exercise treadmill test results. This suggests that a multiple biomarker approach in the diagnosis of coronary artery disease in stable angina patients could be successful. Different aspects of the cardiovascular continuum can be applied to diagnosis and prognostication of cardiovascular disease.
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