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Guanidino compound ratios are associated with stroke etiology, internal carotid artery stenosis and CHA

Authors :
Kathrin, Cordts
Ricarda, Grzybowski
Susanne, Lezius
Nicole, Lüneburg
Dorothee, Atzler
Axel, Neu
Sönke, Hornig
Rainer H, Böger
Christian, Gerloff
Tim, Magnus
Götz, Thomalla
Edzard, Schwedhelm
Peter J, Grant
Chi-Un, Choe
Source :
Journal of the neurological sciences. 397
Publication Year :
2018

Abstract

Guanidino compounds, including l-homoarginine (l-hArg), symmetric dimethylarginine (SDMA), asymmetric dimethylarginine (ADMA) and l-arginine (l-Arg) are associated with mortality, fatal strokes, stroke incidence, and atherosclerosis.We aimed to study the association of guanidino compounds (l-hArg/ADMA and l-hArg/SDMA) with stroke etiology, internal carotid artery (ICA) stenosis and CHAWe analyzed l-hArg, SDMA, ADMA, l-Arg, and compound molar ratios, i.e. l-hArg/ADMA and l-hArg/SDMA, in 272 patients with cerebrovascular disease in a cross-sectional discovery cohort and two cross-sectional validation cohorts of acute stroke patients from Germany (n = 137) and UK (n = 394). The guanidino compound levels were compared with clinical, imaging, and ultrasound parameters.Low l-hArg/ADMA and l-hArg/SDMA molar ratios predicted territorial infarcts (OR 1.74; 95% CI 1.34-2.26 and OR 1.64; 95% CI 1.26-2.15, respectively) and were associated with stroke subtypes due to large vessel disease or cardio-embolism (OR 1.52; 95% CI 1.12-2.06 and OR 2.01; 95% CI 1.35-3.00, respectively) in meta-analysis of the discovery and validation cohort data. In line with these results, a low l-hArg/ADMA and l-hArg/SDMA molar ratio was found in patients with ICA stenosis (OR 0.73; 95% CI 0.55-0.97 and OR 0.69; 95% CI 0.50-0.94, respectively) in the discovery and validation cohort. Furthermore, guanidino compound ratios (i.e. l-hArg/ADMA and l-hArg/SDMA) were strongly correlated with CHAThe results from these three cross-sectional studies reveal that guanidino compound ratios (i.e. l-hArg/ADMA and l-hArg/SDMA) can discriminate stroke etiologies, predict ICA stenosis and estimate risk prediction in patients with cerebrovascular disease.

Details

ISSN :
18785883
Volume :
397
Database :
OpenAIRE
Journal :
Journal of the neurological sciences
Accession number :
edsair.pmid..........3d160ead32346fa0524fc861cb3430ba