Chaofu Ke1, Chen-Wei Pan2, Yuxia Zhang1, Xiaohong Zhu3, Yonghong Zhang4. 1. Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, People's Republic of China. 2. School of Public Health, Medical College of Soochow University, Suzhou, 215123, China. 3. Suzhou Industrial Park Centers for Disease Control and Prevention (Institute of Health Inspection and Supervision), Suzhou, 215021, Jiangsu, People's Republic of China. 4. Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, People's Republic of China. yhzhang@suda.edu.cn.
Abstract
INTRODUCTION: Ischemic stroke (IS) is a major contributor to the global disease burden, and effective biomarkers for IS management in clinical practice are urgently needed. Metabolomics can detect metabolites that are small enough to cross the blood-brain barrier in a high-throughput manner, and thus represents a powerful tool for discovering biomarkers of IS. OBJECTIVES: In this study, we conducted a systematic review to identify potential metabolic biomarkers and pathways that might facilitate risk predictions, clinical diagnoses, the recognition of complications, predictions of recurrence and an understanding of the pathogenesis of IS. METHODS: The PubMed and Web of Science databases were searched for relevant studies published between January 2000 and July 2019. The study objectives, study designs and reported metabolic biomarkers were systematically examined and compared. Pathway analysis was performed using the MetaboAnalyst online software. RESULTS: Twenty-eight studies were included in this systematic review. Many consistent metabolites, including isoleucine, leucine, valine, glycine, lysine, glutamate, LysoPC(16:0), LysoPC(18:2), serine, uric acid, citrate and palmitic acid, possess potential as biomarkers of IS. Metabolic pathways and dysregulations that are implicated in excitotoxicity, inflammation, apoptosis, oxidative stress, neuroprotection, energy failure, and elevation of intracellular Ca2+ levels, were indicated as playing important roles in the development and progression of IS. CONCLUSIONS: This systematic review summarizes potential metabolic biomarkers and pathways related to IS, which may provide opportunities for the construction of diagnostic or predictive models for IS and the discovery of novel therapeutic targets.
INTRODUCTION:Ischemic stroke (IS) is a major contributor to the global disease burden, and effective biomarkers for IS management in clinical practice are urgently needed. Metabolomics can detect metabolites that are small enough to cross the blood-brain barrier in a high-throughput manner, and thus represents a powerful tool for discovering biomarkers of IS. OBJECTIVES: In this study, we conducted a systematic review to identify potential metabolic biomarkers and pathways that might facilitate risk predictions, clinical diagnoses, the recognition of complications, predictions of recurrence and an understanding of the pathogenesis of IS. METHODS: The PubMed and Web of Science databases were searched for relevant studies published between January 2000 and July 2019. The study objectives, study designs and reported metabolic biomarkers were systematically examined and compared. Pathway analysis was performed using the MetaboAnalyst online software. RESULTS: Twenty-eight studies were included in this systematic review. Many consistent metabolites, including isoleucine, leucine, valine, glycine, lysine, glutamate, LysoPC(16:0), LysoPC(18:2), serine, uric acid, citrate and palmitic acid, possess potential as biomarkers of IS. Metabolic pathways and dysregulations that are implicated in excitotoxicity, inflammation, apoptosis, oxidative stress, neuroprotection, energy failure, and elevation of intracellular Ca2+ levels, were indicated as playing important roles in the development and progression of IS. CONCLUSIONS: This systematic review summarizes potential metabolic biomarkers and pathways related to IS, which may provide opportunities for the construction of diagnostic or predictive models for IS and the discovery of novel therapeutic targets.
Authors: Raul Sanchez-Gimenez; Wahiba Ahmed-Khodja; Yesica Molina; Oscar M Peiró; Gil Bonet; Anna Carrasquer; George A Fragkiadakis; Mònica Bulló; Alfredo Bardaji; Christopher Papandreou Journal: Nutrients Date: 2022-06-27 Impact factor: 6.706
Authors: Ilias Thomas; Alex M Dickens; Jussi P Posti; Endre Czeiter; Daniel Duberg; Tim Sinioja; Matilda Kråkström; Isabel R A Retel Helmrich; Kevin K W Wang; Andrew I R Maas; Ewout W Steyerberg; David K Menon; Olli Tenovuo; Tuulia Hyötyläinen; András Büki; Matej Orešič Journal: Nat Commun Date: 2022-05-10 Impact factor: 17.694
Authors: Leonidas Mavroudakis; Susan L Stevens; Kyle D Duncan; Mary P Stenzel-Poore; Julia Laskin; Ingela Lanekoff Journal: Anal Bioanal Chem Date: 2020-10-19 Impact factor: 4.142