Details

Autor(en) / Beteiligte

• von zur Mühlen, Constantin
• Koeck, Thomas
• Schiffer, Eric
• Sackmann, Christine
• Zürbig, Petra
• Hilgendorf, Ingo
• Reinöhl, Jochen
• Rivera, Jennifer
• Zirlik, Andreas
• Hehrlein, Christoph
• Mischak, Harald
• Bode, Christoph
• Peter, Karlheinz

Titel

Urine proteome analysis as a discovery tool in patients with deep vein thrombosis and pulmonary embolism

Ist Teil von

• Proteomics. Clinical applications, 2016-05, Vol.10 (5), p.574-584

Ort / Verlag

Germany: Blackwell Publishing Ltd

Erscheinungsjahr

2016

Quelle

MEDLINE

Beschreibungen/Notizen

• Purpose Early and accurate detection of deep vein thrombosis (DVT) is an important clinical need. Based on the hypothesis that urinary peptides may hold information on DVT in conjunction with pulmonary embolism (PE), the study was aimed at identifying such peptide biomarkers using capillary electrophoresis coupled mass spectrometry. Experimental design Patients with symptoms of unprovoked/idiopathic DVT and/or PE were examined by doppler‐sonography or angio‐computed tomography. Urinary proteome analysis allowed for identification of respective peptide biomarkers. To confirm their biological relevance, we induced PE in mice and assessed human ex vivo thrombi. Results We identified 62 urinary peptides as DVT‐specific biomarkers, i.e. fragments of collagen type I and a fragment of fibrinogen β‐chain. The presence of fibrinogen α/β in the acute thrombus, and collagen type I and osteopontin in the older, organized thrombus was demonstrated. The classifier DVT62 established through support vector machine (SVM) modeling based on the 62 identified peptides was validated in an independent cohort of 47 subjects (six cases and 41 controls) with a sensitivity of 100% and specificity of 83%. Conclusions and clinical relevance Urine proteome analysis enabled the detection of DVT‐specific peptides, which were validated in human and mouse tissue. Furthermore, it allowed for the establishment of an urinary‐proteome based classifier that is relatively specific for DVT. The data provide the basis for assessment of these biomarkers in a prospective clinical study.