Relations of growth-differentiation factor-15 to biomarkers reflecting vascular pathologies in a population-based sample of elderly subjects.
BACKGROUND
Growth-differentiation factor-15 (GDF-15) has recently emerged as a risk predictor in patients with cardiac diseases. GDF-15 is commonly related to cardiovascular risk factors, inflammatory activity and cardiac abnormalities. However, it is not clear whether it might be an indicator of vascular pathologies as well.


METHODS
Circulating levels of GDF-15 were measured in 1004 elderly community dwellers participating in the PIVUS study. The relations of GDF-15 to biomarkers of endothelial activation (E-selectin, P-selectin, ICAM-1, VCAM-1), extracellular matrix degradation (MMP-9, TIMP-1), coagulatory activity (D-dimer, von Willebrand factor, prothrombin fragment 1 + 2, factor VIIa), and fibrinolytic activity (PAI-1 activity, tPA-antigen) were assessed by multiple linear regressions.


RESULTS
The median GDF-15 level was 1135 ng/L. By linear correlation analysis, GDF-15 exhibited a moderate relation to von Willebrand factor (r = 0.30), and weak, albeit significant relations (r = 0.13-0.29) to E-selectin, P-selectin, ICAM-1, VCAM-1, MMP-9, TIMP-1, D-dimer, PAI-1 activity and tPA-antigen. The relations to the assessed biomarkers of endothelial activation, TIMP-1, D-dimer and von Willebrand factor remained significant applying multiple linear regression models adjusted for clinical covariates and echocardiographic data. There were no significant relations between GDF-15 and biomarkers solely reflecting coagulatory activity.


CONCLUSIONS
In the elderly, GDF-15 reflects endothelial activation and vascular inflammation and thus, multiple pathways involved in the development and progression of atherosclerosis.
Department of Medical Sciences (Cardiology and Clinical Chemistry) and Clinical Research Center, Uppsala University, Uppsala, Sweden. kai.eggers@ucr.uu.se
Kai M
KM
Eggers
Tibor
T
Kempf
Lars
L
Lind
Johan
J
Sundström
Lars
L
Wallentin
Kai C
KC
Wollert
Agneta
A
Siegbahn
D000368:Aged; D050197:Atherosclerosis / Q000097:blood* / Q000473:pathology; D015415:Biomarkers / Q000097:blood; D001777:Blood Coagulation; D001798:Blood Proteins / Q000378:metabolism*; D042783:Endothelial Cells / Q000378:metabolism; D004730:Endothelium, Vascular / Q000378:metabolism / Q000473:pathology; D005109:Extracellular Matrix / Q000378:metabolism; D005260:Female; D005342:Fibrinolysis; D055436:Growth Differentiation Factor 15 / Q000097:blood*; D006801:Humans; D007249:Inflammation / Q000097:blood / Q000473:pathology; D016014:Linear Models; D008297:Male; D020780:Matrix Metalloproteinase 9 / Q000097:blood
D015415:Biomarkers; D001798:Blood Proteins; C526140:GDF15 protein, human; D055436:Growth Differentiation Factor 15; D020780:Matrix Metalloproteinase 9