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[16:0]) were significantly associated with SR. Moreover, LysoPC(20:4) also arose as a potential SR biomarker, increasing the prediction power of age, blood pressure, clinical features, duration of symptoms, and diabetes scale (ABCD2) and LAA. Individuals who present early (,3 months) recurrence have a specific metabolomic pattern, differing from non-SR and late SR subjects. Finally, a potential LAA biomarker, LysoPC(22:6), was also described. Conclusions:The use of metabolomics in SR biomarker research improves the predictive power of conventional predictors such as ABCD2 and LAA. Moreover, pattern recognition methods allow us to discriminate not only SR patients but also early and late SR cases. Neurology ® 2015;84:36-45 GLOSSARY ABCD2 5 age, blood pressure, clinical features, duration of symptoms, and diabetes scale; IDI 5 integrated discrimination improvement; LAA 5 large-artery atherosclerosis; Lp-PLA 5 lipoprotein-associated phospholipase A; NRI 5 net reclassification improvement; LysoPC 5 lysophosphatidylcholine; MS/MS 5 tandem mass spectrometry; PLS-DA 5 partial least squares discriminant analysis; ROC 5 receiver operating characteristic; SLC 5 solute carrier; SR 5 stroke recurrence.

Metabolomics Predicts Neuroimaging Characteristics of Transient Ischemic Attack Patients

“…As we have published previously, we did not find any statistically significant differences between the two cohorts based on vascular risk factors, clinical characteristics and neuroimaging data (Jove et al, 2015b). We observed DWI abnormalities in 115 (40.9%) patients.…”

“…As in our previous work (Jove et al, 2015b), specific patterns of LysoPC were again relevant. LysoPC (22:6) and LysoPC (20:4), that were previously related to LAA and stroke recurrence respectively, were now associated with lesion volume.…”

“…Moreover, plasma metabolites levels could be influenced by many factors such as diet, medications, age and clinical variables (Mauri-Capdevila et al, 2013). However, the use of two cohorts allows overcoming these potential limitations, increasing the robustness of the resulting data (Jove et al, 2015a, Shi et al, 2004). A further limitation of the present work is the fact that many molecules where not identified, although it is a common circumstance for these kind of analyses (Vaniya and Fiehn, 2015).…”

“…The main methodology has been previously described (Jove et al, 2015a). We prospectively recruited two independent cohorts of consecutive TIA patients who were attended to by a neurologist during the first 24 h after the onset of symptoms.…”

“…The use of metabolomics on TIA patients has started a new era in biomarker discovering for clinical purpose (Jove et al, 2015a). Metabolomics allows the study of the complete set of low-molecular-weight intermediates (metabolites), which vary according to the pathologic state of the cell, tissue, organ, or organism and are context-dependent (Jove et al, 2014, Mauri-Capdevila et al, 2013).…”