β-Trace Protein: From GFR Marker to Cardiovascular Risk Predictor

β-Trace protein, also known as Lipocalin type prostaglandin D synthase, is a low-molecular mass glycoprotein (between 23,000 and 29,000 Da depending on the degree of glycosylation) that converts prostaglandin H2 into prostaglandin D2. β-Trace protein was initially isolated from cerebrospinal fluid a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Clinical journal of the American Society of Nephrology 2013-05, Vol.8 (5), p.873-881
Hauptverfasser: Orenes-Piñero, Esteban, Manzano-Fernández, Sergio, López-Cuenca, Ángel, Marín, Francisco, Valdés, Mariano, Januzzi, James L.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:β-Trace protein, also known as Lipocalin type prostaglandin D synthase, is a low-molecular mass glycoprotein (between 23,000 and 29,000 Da depending on the degree of glycosylation) that converts prostaglandin H2 into prostaglandin D2. β-Trace protein was initially isolated from cerebrospinal fluid and served as a marker of cerebrospinal fluid leakage; however, its cDNA and gene have been isolated in numerous human body tissues, including central nervous system, retina, melanocytes, heart, and male genital organs. In recent years, β-trace protein has emerged as a promising novel endogenous marker of GFR, representing a more sensitive marker for mild kidney dysfunction than serum creatinine. In this regard, β-trace protein has been proposed as an alternative marker to Cystatin C for measuring kidney function. Beyond its role for estimating renal function, β-trace protein is also emerging as a novel biomarker in cardiovascular risk. It has been associated with several cardiovascular disorders, playing a potential role for prognostic stratification in patients with acutely decompensated heart failure and acute coronary syndromes and being advocated as a novel marker for cardiovascular risk prediction.
ISSN:1555-9041
1555-905X
DOI:10.2215/CJN.08870812