Dataset Information

Succinate links atrial dysfunction and cardioembolic stroke.

ABSTRACT:

Objective

To determine whether altered metabolic profiles represent a link between atrial dysfunction and cardioembolic (CE) stroke, and thus whether underlying dysfunctional atrial substrate may contribute to thromboembolism risk in CE stroke.

Methods

A total of 144 metabolites were measured using liquid chromatography-tandem mass spectrometry in plasma samples collected within 9 hours of stroke onset in 367 acute stroke patients. Stroke subtype was assigned using the Causative Classification of Stroke System, and CE stroke (n = 181) was compared to non-CE stroke (n = 186). Markers of left atrial dysfunction included abnormal atrial function (P-wave terminal force in lead V1, PTFV₁ >4,000 μV·ms), left atrial enlargement on echocardiography, and frank atrial fibrillation on ECG. Stroke recurrence risk was assessed using CHADS₂ and CHA₂DS₂-VASc scores. Associations between metabolites and CE stroke, atrial dysfunction, and stroke recurrence risk were evaluated using logistic regression models.

Results

Three tricarboxylic acid metabolites-succinate (odds ratio [OR] 1.71, 95% confidence interval [CI] 1.36-2.15, p = 1.37 × 10^-6), α-ketoglutarate (OR 1.62, 95% CI 1.29-2.04, p = 1.62 × 10^-5), and malate (OR 1.58, 95% CI 1.26-1.97, p = 2.57 × 10^-5)-were associated with CE stroke. Succinate (OR 1.36, 95% CI 1.31-1.98, p = 1.22 × 10^-6), α-ketoglutarate (OR 2.14, 95% CI 1.60-2.87, p = 2.08 × 10^-8), and malate (OR 2.02, 95% CI 1.53-2.66, p = 1.60 × 10^-7) were among metabolites also associated with subclinical atrial dysfunction. Of these, succinate was also associated with left atrial enlargement (OR 1.54, 95% CI 1.23-1.94, p = 1.06 × 10^-4) and stroke recurrence based on dichotomized CHADS₂ (OR 2.63, 95% CI 1.68-4.13, p = 3.00 × 10^-6) and CHA₂DS₂-VASc (OR 2.43, 95% CI 1.60-3.68, p = 4.25 × 10^-6) scores.

Conclusions

Metabolite profiling identified changes in succinate associated with CE stroke, atrial dysfunction, and stroke recurrence, revealing a putative underlying link between CE stroke and energy metabolism.

SUBMITTER: Nelson SE

PROVIDER: S-EPMC6396969 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background and Purpose- Classification of stroke as cardioembolic in etiology can be challenging, particularly since the predominant cause, atrial fibrillation (AF), may not be present at the time of stroke. Efficient tools that discriminate cardioembolic from noncardioembolic strokes may improve care as anticoagulation is frequently indicated after cardioembolism. We sought to assess and quantify the discriminative power of AF risk as a classifier for cardioembolism in a real-world population of patients with acute ischemic stroke. Methods- We performed a cross-sectional analysis of a multi-institutional sample of patients with acute ischemic stroke. We systematically adjudicated stroke subtype and examined associations between AF risk using CHA2DS2-VASc, Cohorts for Heart and Aging Research in Genomic Epidemiology-AF score, and the recently developed Electronic Health Record-Based AF score, and cardioembolic stroke using logistic regression. We compared the ability of AF risk to discriminate cardioembolism by calculating C statistics and sensitivity/specificity cutoffs for cardioembolic stroke. Results- Of 1431 individuals with ischemic stroke (age, 65±15; 40% women), 323 (22.6%) had cardioembolism. AF risk was significantly associated with cardioembolism (CHA2DS2-VASc: odds ratio [OR] per SD, 1.69 [95% CI, 1.49-1.93]; Cohorts for Heart and Aging Research in Genomic Epidemiology-AF score: OR, 2.22 [95% CI, 1.90-2.60]; electronic Health Record-Based AF: OR, 2.55 [95% CI, 2.16-3.04]). Discrimination was greater for Cohorts for Heart and Aging Research in Genomic Epidemiology-AF score (C index, 0.695 [95% CI, 0.663-0.726]) and Electronic Health Record-Based AF score (0.713 [95% CI, 0.681-0.744]) versus CHA2DS2-VASc (C index, 0.651 [95% CI, 0.619-0.683]). Examination of AF scores across a range of thresholds indicated that AF risk may facilitate identification of individuals at low likelihood of cardioembolism (eg, negative likelihood ratios for Electronic Health Record-Based AF score ranged 0.31-0.10 at sensitivity thresholds 0.90-0.99). Conclusions- AF risk scores associate with cardioembolic stroke and exhibit moderate discrimination. Utilization of AF risk scores at the time of stroke may be most useful for identifying individuals at low probability of cardioembolism. Future analyses are warranted to assess whether stroke subtype classification can be enhanced to improve outcomes in undifferentiated stroke.