Heart failure is a critical, clinical diagnosis characterized by shortness of breath at rest, fatigue, weakness and edema. Only 50% of patients are alive 5 years after diagnosis. In Denmark, 61,000 live with heart failure, and 12,000 are diagnosed with the disease every year. Two categories exists: heart failure with reduced or with preserved ejection fraction (HFrEF and HFpEF, respectively). HFrEF is caused by a weakened heart muscle, whereas HFpEF hearts are too stiff to be filled sufficiently during diastole. Historically, focus has been on HFrEF, but HFpEF represents an unmet medical need due to the unknown underlying causes, and the lack of efficient, clinical treatment options.
Patients with HFpEF have debilitating symptoms (shortness of breath, fatigue, severe weakness and edema), despite the contractile force of the heart is being maintained. Elevated left ventricular filling pressures can in part compensate for diastolic dysfunction, but this comes with the risk of pulmonary congestion.
We have developed a mouse model of HFpEF in order to understand disease progression. We have a proteomic analysis of samples from the left atrium and left ventricle. The left atrium is subject to the elevated filling pressures. The left ventricle stiff and hypertrophic. You will use your knowledge about big data analysis and your physiological insights to analyze this data set and produce testable hypotheses about the chamber-specific changes that occurs during the disease development.