UNDERSTANDING THE CO-VARIATION OF MAIN CARDIOVASCULAR DISEASES BY USE OF GENOMICS, PROTEOMICS AND METABOLOMICS

Title [sv]

Abstract [sv]

Background: The four major cardiovascular diseases (CVD) are myocardial infarction, stroke, heart failure and atrial fibrillation. Over time, many patients suffer from more than one of these diseases possibly because of shared pathophysiology, such as atherosclerosis, but the molecular mechanisms underlying other shared pathophysiological pathways than atherosclerosis remains to be characterized.Aim: To use large-scale population-based studies to investigate the co-variation of major CVDs and to use genomics, proteomic and metabolomics to find new pathophysiological pathways linked to more than one CVD. The hypothesis tested is that we by these actions will find new pathways that will improve the understanding of the pathophysiology of CVDs, as well as improve risk prediction. Workplan: To use a population-based study (X-69, 18,000 individuals) with 50 years follow-up to study the co-variation between CVDs over the adult life-span. In the large-scale UK biobank (500,000 individuals), we will use genetics, proteomics and metabolomics to investigate the molecular basis of pathophysiological pathways underlying one or more of these diseases. Traditional statistical methods, as well as machine learning methods will be applied. To further characterize such pathways, the interesting proteins/metabolites will be evaluated vs subclinical markers of disease, such as atherosclerosis in the carotid and coronary arteries, arterial stiffness, myocardial and endothelial function in separate studies (SCAPIS, PIVUS, POEM). Mendelian randomization will be used to assess causality of the found associations. C-statistics will be used to determine if the use of proteomics and metabolomics would increase the predictive power compared to traditional CVD risk factors.Significance: The molecular characterization of pathophysiological pathways being involved in more than one CVD could lead to new targets for drug development, as well as improved risk prediction.

Abstract [en]

Background: The four major cardiovascular diseases (CVD) are myocardial infarction, stroke, heart failure and atrial fibrillation. Over time, many patients suffer from more than one of these diseases possibly because of shared pathophysiology, such as atherosclerosis, but the molecular mechanisms underlying other shared pathophysiological pathways than atherosclerosis remains to be characterized.Aim: To use large-scale population-based studies to investigate the co-variation of major CVDs and to use genomics, proteomic and metabolomics to find new pathophysiological pathways linked to more than one CVD. The hypothesis tested is that we by these actions will find new pathways that will improve the understanding of the pathophysiology of CVDs, as well as improve risk prediction. Workplan: To use a population-based study (X-69, 18,000 individuals) with 50 years follow-up to study the co-variation between CVDs over the adult life-span. In the large-scale UK biobank (500,000 individuals), we will use genetics, proteomics and metabolomics to investigate the molecular basis of pathophysiological pathways underlying one or more of these diseases. Traditional statistical methods, as well as machine learning methods will be applied. To further characterize such pathways, the interesting proteins/metabolites will be evaluated vs subclinical markers of disease, such as atherosclerosis in the carotid and coronary arteries, arterial stiffness, myocardial and endothelial function in separate studies (SCAPIS, PIVUS, POEM). Mendelian randomization will be used to assess causality of the found associations. C-statistics will be used to determine if the use of proteomics and metabolomics would increase the predictive power compared to traditional CVD risk factors.Significance: The molecular characterization of pathophysiological pathways being involved in more than one CVD could lead to new targets for drug development, as well as improved risk prediction.

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Uppsala University

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Hjärt-Lungfonden

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