Nat Rev Neurol: a multi group review of stroke biomarkers and therapeutic targets
Last Update: 2020-06-19
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< br / > < br / >Among them, ischemic < br / > Stroke < br / > is the most common type, accounting for 87% of all strokesHowever, there is no biomarker for clinical use, which challenges the early diagnosis and treatment of stroke patientsThe rapid development of high-throughput technology and bioinformatics provides a new opportunity to decipher the pathophysiology of this complex diseaseThrough the integration of multi group technology, we can simultaneously study thousands of proteins (proteomics), genes (genomics), RNA (transcriptome) and metabolites (metabonomics), and then reveal the interaction network between them at the molecular level< br / > < br / > in this review, the author introduces in detail the knowledge of stroke pathology and the research status of biomarkersIn addition, proteomics, metabonomics, transcriptomics and genomics will provide useful help for the discovery of stroke pathogenesis, therapeutic targets and biomarkers< br / > < br / > in this review, the authors outline the use of multi-component techniques to help identify biomarkers for the diagnosis and prognosis of ischemic stroke and how they identify molecular targets for therapeutic interventions (Figure 1)In this paper, we study the progress in genomics, transcriptome, proteomics and metabonomics in recent years, and discuss how to combine data from these technologies through integration and systems biology to promote the understanding of stroke< br / > < br / > 1Pathophysiology of ischemic stroke < br / > < br / > in acute ischemic stroke, the sudden decrease of cerebral blood flow will lead to the decrease of oxygen and glucose supply of neurons and other brain cells in whole or in partThe result is to trigger a variety of physiological, biochemical and molecular mechanisms, eventually leading to a large number of cell death and change the basic nerve function of ischemic nucleusDead brain cells release dangerous signals, known as damage-related molecular patterns (damps)Damps and proinflammatory cytokines activate primary and secondary lymphoid organs, leading to systemic inflammatory response syndromeTherefore, the changes of < br / > immunity after stroke are not only limited to the brain, but also occur in various peripheral organs, including blood, bone marrow, spleen and intestine< br / > < br / > however, the inflammatory response after stroke is self limiting, and excessive proinflammatory mediators can also activate the sympathetic and hypothalamic pituitary adrenal axisymmetric systemsThese systems release stress hormones, glucocorticoids and catecholamines, which promote the apoptosis of < br / > immune < br / > cells, increase the production of anti-inflammatory cytokines, such as transforming growth factor - β (TGF β), and inhibit the production of inflammatory mediators such as IL-1, IL-8 and tumor necrosis factor (TNF) Among the thousands of molecules changed in these processes, some may be valuable disease indicators, which will contribute to the diagnosis and prognosis of ischemic stroke At present, some valuable molecules have been identified by using high-throughput technology < br / > With the development of research, some candidate markers with specific clinical indications have emerged and may be used in the future Compared with the future stroke care based on biomarkers, the current stroke < br / > prevention < br / > and treatment nursing standards < br / > and acute ischemic stroke < br / > < br / > the research on biomarkers of acute stroke mainly focuses on two aspects: the first is to improve or accelerate the diagnosis Second, improve clinical decision-making and promote the use of personalized treatment At present, stroke is diagnosed by clinical evaluation and neuroimaging Faster and more accurate stroke diagnosis technology, such as blood test, is very important for early treatment In previous studies, the effectiveness of a single biomarker or biomarker panel in this case has been evaluated, but its accuracy is far lower than the requirements of clinical practice Biomarkers for diagnosis of TIA are also valuable because many patients are asymptomatic at the time of treatment, so diagnosis mainly depends on clinical history In addition, biomarkers for predicting therapeutic response are becoming more and more important because different patients respond differently to intravenous thrombolysis and mechanical reperfusion Several studies have shown that there is a correlation between the transformation of hemorrhage and the increase of circulating matrix metalloproteinase-9 (MMP9), which plays a key role in microvascular and blood-brain barrier integrity < br / > < br / > 2 Other non acute ischemic stroke < br / > < br / > even if the basic characteristics of patients are similar, there are differences in the prognosis after several months Many molecular markers are associated with these results Many molecular markers are associated with these results For example, the level of inflammatory biomarkers such as IL-6 and peptide has a higher predictive value for prognosis than clinical variables However, in addition to predicting the overall prognosis, blood biomarkers can also provide information on the specific causes of complications leading to poor prognosis In the patients with ischemic stroke, despite extensive examination, 25% - 30% of the patients were discharged without definite diagnosis of the cause of stroke Paroxysmal atrial fibrillation is considered to be a potential cause of these patients, especially those with unexplained thrombotic stroke < br / > < br / > 3 Standardization of biomarker detection < br / > < br / > although some biomarkers may be close to the clinical stage, their application in clinical practice needs further research due to the sources of variability before and during the analysis Pre analysis sources include sample storage conditions and time, freeze-thaw cycles, types of biological samples (e.g., serum, plasma, and other liquids), and biological variations of biomarkers in health and disease situations Analytical variability is introduced by factors related to analytical methods, such as analytical design, differences in antibodies (used as reagents) or correctors (usually recombinant proteins or synthetic peptides used to calibrate immunoassays) The use of nonstandard methods in clinical research may lead to inaccurate conclusions about the value of biomarkers, and ultimately lead to wrong clinical decisions In order to solve this problem, once the standardization or coordination is completed, the old measurement methods from clinical and epidemiological studies to gold standard reference measurement will be recalibrated This approach will enable meta-analysis to produce strong conclusions in support of clinical decision-making In addition, the standardization of clinical data can make cross trial data analysis possible; the larger sample size generated by this possibility will provide enough motivation for the study subgroup, which can not be explored in a single trial < br / > However, advances in technology have enabled the use of high-throughput technologies based on large-scale screening processes, and generated a large number of candidate molecules for evaluation as biomarkers < br / > However, genomics, transcriptomics and metabonomics are producing more and more promising results, and these multi group methods may be complementary, especially if multiple group methods can be applied to the same patient < br / > In clinical stroke research, the rapid development of proteomics technology has been used to better understand the pathophysiology of the disease, so as to identify many potential biomarkers (Table 2) < br / > < br / / > proteomics of ischemic brain < br / > < br / > in the first study on proteomics of stroke patients published in 2009, Laser microanatomy is used to study the expression profile of MMP in neurons and vascular system of ischemic brain This study shows that neurons are an important source of MMP10 after stroke, while the content of vascular MMP9 and tissue inhibitor of metalloproteinase-2 (TIMP2) is high In a study published in 2018, recent advances in proteomics enabled us to assess the protein level response of each component of the neurovascular unit to ischemic events < br / > < br / > proteomics in body fluids after stroke < br / > < br / > in addition to the study of brain proteomics, the protein expression patterns in available body fluids were also studied, so as to better understand the pathophysiology of ischemic stroke In 2011, a few months after the first description of the human brain proteome, the study of the brain extracellular fluid proteome of stroke patients was also published for the first time < br / > < br / > the great progress of neurovascular proteomics makes us closer to the biomarkers of diagnosis, prognosis and treatment of ischemic stroke However, no potential biomarkers have been found to be transformed into clinical tools The main reason for this difference is that proteomics research is based on a universal hypothesis However, this hypothesis is flawed, because the different responses of patients to treatment are caused by many factors, including gene and individual proteomics We also hope that the biomarker field will develop towards < br / > precise < br / > medical treatment, and the differences between individuals will be taken into account when choosing the right treatment method In this case, proteomics can recognize thousands of proteins and their related post-translational modifications This makes it an ideal strategy to find new biomarkers quickly, and has high precision and prediction ability Patient centered protein biomarkers will enable patients to be better stratified for appropriate treatment at the right dose and at the best time However, the number of patients needed for large-scale proteomics research and the high cost of equipment are also the reasons that hinder rapid clinical application Because of the heterogeneity of stroke, it has been proved that its genomics is more complex than other common vascular and nervous system diseases Multi generation collaboration has made important progress in population-based and clinical based research This work has a new understanding of the pathophysiology of stroke and opened up a new way for the new treatment In the vast majority of cases, genetic risk variation leads to multifactor susceptibility to stroke, and each genetic variation only leads to a small increase in stroke risk < br / > < br / > the relationship between stroke genes and the development of treatment strategies < br / > < br / > the identification of stroke related genes can help to find and develop new treatment targets and treatment strategies in many aspects, and provide information for the development of new therapies by deciphering the molecular mechanism of stroke risk In addition, accelerate the recognition of genes related to the occurrence and severity of stroke and test them as biological targets This approach requires extensive bioinformatics analysis to identify correlations
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