Metabolomics predicts stroke recurrence after transient ischemic attack.

ABSTRACT:

Objective

To discover, by using metabolomics, novel candidate biomarkers for stroke recurrence (SR) with a higher prediction power than present ones.

Methods

Metabolomic analysis was performed by liquid chromatography coupled to mass spectrometry in plasma samples from an initial cohort of 131 TIA patients recruited <24 hours after the onset of symptoms. Pattern analysis and metabolomic profiling, performed by multivariate statistics, disclosed specific SR and large-artery atherosclerosis (LAA) biomarkers. The use of these methods in an independent cohort (162 subjects) confirmed the results obtained in the first cohort.

Results

Metabolomics analyses could predict SR using pattern recognition methods. Low concentrations of a specific lysophosphatidylcholine (LysoPC[16

SUBMITTER: Jove M 

PROVIDER: S-EPMC4336096 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature