PathBank 2.0-the pathway database for model organism metabolomics.

PathBank (https://pathbank.org) and its predecessor database, the Small Molecule Pathway Database (SMPDB), have been providing comprehensive metabolite pathway information for the metabolomics community since 2010. Over the past 14 years, these pathway databases have grown and evolved significantly to meet the needs of the metabolomics community and respond to continuing changes in computing technology. This year's update, PathBank 2.0, brings a number of important improvements and upgrades that should make the database more useful and more appealing to a larger cross-section of users. In particular, these improvements include: (i) a significant increase in the number of primary or canonical pathways (from 1720 to 6951); (ii) a massive increase in the total number of pathways (from 110 234 to 605 359); (iii) significant improvements to the quality of pathway diagrams and pathway descriptions; (iv) a strong emphasis on drug metabolism and drug mechanism pathways; (v) making most pathway images more slide-compatible and manuscript-compatible; (vi) adding tools to support better pathway filtering and selecting through a more complete pathway taxonomy; (vii) adding pathway analysis tools for visualizing and calculating pathway enrichment. Many other minor improvements and updates to the content, the interface and general performance of the PathBank website have also been made. Overall, we believe these upgrades and updates should greatly enhance PathBank's ease of use and its potential applications for interpreting metabolomics data.

Aging Immune System in Acute Ischemic Stroke: A Transcriptomic Analysis.

[Figure: see text].

RNA expression studies in stroke: what can they tell us about stroke mechanism?

PURPOSE OF REVIEW: Diagnosis of stroke and understanding the mechanism of stroke is critical to implement optimal treatment. RNA expressed in peripheral blood cells is emerging as a precision biomarker to aid in stroke diagnosis and prediction of stroke cause. In this review, we summarize available data regarding the role of RNA to predict stroke, the rationale for these changes, and a discussion of novel mechanistic insight and clinical applications. RECENT FINDINGS: Differences in RNA gene expression in blood have been identified in patients with stroke, including differences to distinguish ischemic from hemorrhagic stroke, and differences between cardioembolic, large vessel atherosclerotic, and small vessel lacunar stroke cause. Gene expression differences show promise as novel stroke biomarkers to predict stroke of unclear cause (cryptogenic stroke). The differences in RNA expression provide novel insight to stroke mechanism, including the role of immune response and thrombosis in human stroke. Important insight to regulation of gene expression in stroke and its causes are being acquired, including alternative splicing, noncoding RNA, and microRNA. SUMMARY: Improved diagnosis of stroke and determination of stroke cause will improve stroke treatment and prevention. RNA biomarkers show promise to aid in the diagnosis of stroke and cause determination, as well as providing novel insight to mechanism of stroke in patients. While further study is required, an RNA profile may one day be part of the stroke armamentarium with utility to guide acute stroke therapy and prevention strategies and refine stroke phenotype.

Association of Thrombin Generation With Leukocyte Inflammatory Profile in Patients With Acute Ischemic Stroke.

BACKGROUND AND OBJECTIVES: Thrombosis is central to the pathogenesis of acute ischemic stroke, with higher thrombin generation being associated with increased stroke risk. The immune system may contribute to thrombin generation in stroke and thus may offer novel strategies for stroke prevention. This study addresses the research question regarding the relationship of thrombin generation to leukocyte gene expression in patients with acute ischemic stroke. METHODS: We isolated RNA from whole blood and examined the relationship to thrombin generation capacity in patients with acute ischemic stroke. Due to its effects on thrombin generation, patients on anticoagulants were excluded from the study. The relationship of gene expression with peak thrombin was evaluated by analysis of covariance across peak thrombin quartiles adjusted for sex and age. RESULTS: In 97 patients with acute ischemic stroke, peak thrombin was variable, ranging from 252.0 to 752.4 nM. Increased peak thrombin was associated with differences in thromboinflammatory leukocyte gene expression, including a decrease in ADAM metallopeptidase with thrombospondin type 1 motif 13 and an increase in nuclear factor κB (NF-κB)-activating protein, protein disulfide isomerase family A member 5, and tissue factor pathway inhibitor 2. Pathways associated with peak thrombin included interleukin 6 signaling, thrombin signaling, and NF-κB signaling. A linear discriminant analysis model summarizing the immune activation associated with peak thrombin in a first cohort of stroke could distinguish patients with low peak thrombin from high peak thrombin in a second cohort of 112 patients with acute ischemic stroke. DISCUSSION: The identified genes and pathways support a role of the immune system contributing to thrombus formation in patients with stroke. These may have relevance to antithrombotic strategies for stroke prevention.

Hemorrhagic Transformation in Ischemic Stroke and the Role of Inflammation.

Hemorrhagic transformation (HT) is a common complication in patients with acute ischemic stroke. It occurs when peripheral blood extravasates across a disrupted blood brain barrier (BBB) into the brain following ischemic stroke. Preventing HT is important as it worsens stroke outcome and increases mortality. Factors associated with increased risk of HT include stroke severity, reperfusion therapy (thrombolysis and thrombectomy), hypertension, hyperglycemia, and age. Inflammation and the immune system are important contributors to BBB disruption and HT and are associated with many of the risk factors for HT. In this review, we present the relationship of inflammation and immune activation to HT in the context of reperfusion therapy, hypertension, hyperglycemia, and age. Differences in inflammatory pathways relating to HT are discussed. The role of inflammation to stratify the risk of HT and therapies targeting the immune system to reduce the risk of HT are presented.

Non-stenotic Carotid Plaques in Embolic Stroke of Unknown Source.

Embolic stroke of unknown source (ESUS) represents one in five ischemic strokes. Ipsilateral non-stenotic carotid plaques are identified in 40% of all ESUS. In this narrative review, we summarize the evidence supporting the potential causal relationship between ESUS and non-stenotic carotid plaques; discuss the remaining challenges in establishing the causal link between non-stenotic plaques and ESUS and describe biomarkers of potential interest for future research. In support of the causal relationship between ESUS and non-stenotic carotid plaques, studies have shown that plaques with high-risk features are five times more prevalent in the ipsilateral vs. the contralateral carotid and there is a lower incidence of atrial fibrillation during follow-up in patients with ipsilateral non-stenotic carotid plaques. However, non-stenotic carotid plaques with or without high-risk features often coexist with other potential etiologies of stroke, notably atrial fibrillation (8.5%), intracranial atherosclerosis (8.4%), patent foramen ovale (5-9%), and atrial cardiopathy (2.4%). Such puzzling clinical associations make it challenging to confirm the causal link between non-stenotic plaques and ESUS. There are several ongoing studies exploring whether select protein and RNA biomarkers of plaque progression or vulnerability could facilitate the reclassification of some ESUS as large vessel strokes or help to optimize secondary prevention strategies.