Exosome-transported lncRNA H19 regulates insulin-like growth factor-1 via the H19/let-7a/insulin-like growth factor-1 receptor axis in ischemic stroke

Non-coding RNAs in acute ischemic stroke: from brain to periphery

Acute ischemic stroke is a clinical emergency and a condition with high morbidity, mortality, and disability. Accurate predictive, diagnostic, and prognostic biomarkers and effective therapeutic targets for acute ischemic stroke remain undetermined. With innovations in high-throughput gene sequencing analysis, many aberrantly expressed non-coding RNAs (ncRNAs) in the brain and peripheral blood after acute ischemic stroke have been found in clinical samples and experimental models. Differentially expressed ncRNAs in the post-stroke brain were demonstrated to play vital roles in pathological processes, leading to neuroprotection or deterioration, thus ncRNAs can serve as therapeutic targets in acute ischemic stroke. Moreover, distinctly expressed ncRNAs in the peripheral blood can be used as biomarkers for acute ischemic stroke prediction, diagnosis, and prognosis. In particular, ncRNAs in peripheral immune cells were recently shown to be involved in the peripheral and brain immune response after acute ischemic stroke. In this review, we consolidate the latest progress of research into the roles of ncRNAs (microRNAs, long ncRNAs, and circular RNAs) in the pathological processes of acute ischemic stroke-induced brain damage, as well as the potential of these ncRNAs to act as biomarkers for acute ischemic stroke prediction, diagnosis, and prognosis. Findings from this review will provide novel ideas for the clinical application of ncRNAs in acute ischemic stroke.

Exosomes: A Cellular Communication Medium That Has Multiple Effects On Brain Diseases

Exosomes, as membranous vesicles generated by multiple cell types and secreted to extracellular space, play a crucial role in a range of brain injury-related brain disorders by transporting diverse proteins, RNA, DNA fragments, and other functional substances. The nervous system's pathogenic mechanisms are complicated, involving pathological processes like as inflammation, apoptosis, oxidative stress, and autophagy, all of which result in blood-brain barrier damage, cognitive impairment, and even loss of normal motor function. Exosomes have been linked to the incidence and progression of brain disorders in recent research. As a result, a thorough knowledge of the interaction between exosomes and brain diseases may lead to the development of more effective therapeutic techniques that may be implemented in the clinic. The potential role of exosomes in brain diseases and the crosstalk between exosomes and other pathogenic processes were discussed in this paper. Simultaneously, we noted the delicate events in which exosomes as a media allow the brain to communicate with other tissues and organs in physiology and disease, and compiled a list of natural compounds that modulate exosomes, in order to further improve our understanding of exosomes and propose new ideas for treating brain disorders.

Long Non-Coding H19 in Lymphocytes: Prognostic Value in Acute Ischemic Stroke Patients

Acute ischemic stroke (AIS) is a cerebrovascular disease that seriously affects the physical and mental health and quality of life of patients. However, there is a lack of reliable prognostic prediction methods. The main objective of this study was to investigate the prognostic value of long non-coding RNA (lncRNA) H19 in lymphocytes of patients with AIS, and to construct a prognostic prediction model for AIS including lncRNA H19 in lymphocytes, which would provide new ideas for the prognostic evaluation of AIS. Poor prognosis was defined when the patient's modified Rankin scale (mRS) score at 3 months after AIS onset was greater than 2. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to measure the level of lncRNA H19 in lymphocytes. Spearman correlation analysis revealed a positive correlation between lncRNA H19 and mRS score at 3 months after AIS onset (r = 0.1977, p = 0.0032), while lncRNA H19 was negatively correlated with white blood cells counts, lymphocytes counts, and neutrophils counts. Logistic regression analysis identified lncRNA H19 as an independent predictor of poor prognosis (OR = 3.062 [1.69-5.548], p < 0.001). Moreover, a nomogram prediction model incorporating lncRNA H19 in lymphocytes demonstrated effective discrimination, calibration, and clinical applicability in predicting AIS outcomes. The findings suggest that lncRNA H19 in lymphocytes could be a valuable prognostic indicator and a potential pharmacological target for AIS patients, and might be a novel pathway for enhanced prognostic evaluation and targeted therapeutic strategies.

Epigenetics of cerebrovascular diseases: an update review of clinical studies

Cerebrovascular diseases, especially stroke, are critical and heterogenous clinical conditions associated with high mortality and chronic disability. Genome-wide association studies reveal substantial stroke heritability, though specific genetic variants account for a minor fraction of stroke risk, suggesting an essential role for the epigenome. Epigenome-wide association studies and candidate gene approaches show that DNA methylation patterns significantly influence stroke susceptibility. Additionally, chromatin remodelers and non-coding RNA regulate gene expression in response to ischemic conditions. In this updated review, we summarized the progress of knowledge on epigenetics in the field of ischemic stroke underlying opportunities and challenges.

Multicenter Validation of lncRNA and Target mRNA Diagnostic and Prognostic Biomarkers of Acute Ischemic Stroke From Peripheral Blood Leukocytes

BACKGROUND

Long noncoding RNA (lncRNA) and mRNA profiles in leukocytes have shown potential as biomarkers for acute ischemic stroke (AIS). This study aimed to identify altered lncRNA and target mRNA profiles in peripheral blood leukocytes as biomarkers and to assess the diagnostic value and association with AIS prognosis.

METHODS AND RESULTS

Differentially expressed lncRNAs (DElncRNAs) and differentially expressed target mRNAs (DEmRNAs) were screened by RNA sequencing in the discovery set, which consisted of 10 patients with AIS and 20 controls. Validation sets consisted of a multicenter (311 AIS versus 303 controls) and a nested case-control study (351 AIS versus 352 controls). The discriminative value of DElncRNAs and DEmRNAs added to the traditional risk factors was estimated with the area under the curve. NAMPT-AS, FARP1-AS1, FTH1, and NAMPT were identified in the multicenter case-control study (P<0.05). LncRNA NAMPT-AS was associated with cis-target mRNA NAMPT and trans-target mRNA FTH1 in all validation sets (P<0.001). Similarly, AIS cases exhibited upregulated lncRNA FARP-AS1 and FTH1 expression (P<0.001) in the nested case-control study (P<0.001). Furthermore, lncRNA FARP1-AS1 expression was upregulated in AIS patients at discharge with an unfavorable outcome (P<0.001). Positive correlations were found between NAMPT expression level and NIHSS scores of AIS patients (P<0.05). Adding 2 lncRNAs and 2 target mRNAs to the traditional risk factor model improved area under the curve by 22.8% and 5.2% in the multicenter and the nested case-control studies, respectively.

CONCLUSIONS

lncRNA NAMPT-AS and FARP1-AS1 have potential as diagnostic biomarkers for AIS and exhibit good performance when combined with target mRNA NAMPT and FTH1.

The Landscape of Biomimetic Nanovesicles in Brain Diseases

Brain diseases, such as brain tumors, neurodegenerative diseases, cerebrovascular diseases, and brain injuries, are caused by various pathophysiological changes, which pose a serious health threat. Brain disorders are often difficult to treat due to the presence of the blood-brain barrier (BBB). Biomimetic nanovesicles (BNVs), including endogenous extracellular vesicles (EVs) derived from various cells and artificial nanovesicles, possess the ability to penetrate the BBB and thus can be utilized for drug delivery to the brain. BNVs, especially endogenous EVs, are widely distributed in body fluids and usually carry various disease-related signal molecules such as proteins, RNA, and DNA, and may also be analyzed to understand the etiology and pathogenesis of brain diseases. This review covers the exhaustive classification and characterization of BNVs and pathophysiological roles involved in various brain diseases, and emphatically focuses on nanotechnology-integrated BNVs for brain disease theranostics, including various diagnosis strategies and precise therapeutic regulations (e.g., immunity regulation, disordered protein clearance, anti-neuroinflammation, neuroregeneration, angiogenesis, and the gut-brain axis regulation). The remaining challenges and future perspectives regarding the nanotechnology-integrated BNVs for the diagnosis and treatment of brain diseases are also discussed and outlined.

Pharmacological interventions targeting the microcirculation following traumatic spinal cord injury

Traumatic spinal cord injury is a devastating disorder characterized by sensory, motor, and autonomic dysfunction that severely compromises an individual's ability to perform activities of daily living. These adverse outcomes are closely related to the complex mechanism of spinal cord injury, the limited regenerative capacity of central neurons, and the inhibitory environment formed by traumatic injury. Disruption to the microcirculation is an important pathophysiological mechanism of spinal cord injury. A number of therapeutic agents have been shown to improve the injury environment, mitigate secondary damage, and/or promote regeneration and repair. Among them, the spinal cord microcirculation has become an important target for the treatment of spinal cord injury. Drug interventions targeting the microcirculation can improve the microenvironment and promote recovery following spinal cord injury. These drugs target the structure and function of the spinal cord microcirculation and are essential for maintaining the normal function of spinal neurons, axons, and glial cells. This review discusses the pathophysiological role of spinal cord microcirculation in spinal cord injury, including its structure and histopathological changes. Further, it summarizes the progress of drug therapies targeting the spinal cord microcirculation after spinal cord injury.

Integrated plasma and exosome long noncoding RNA profiling is promising for diagnosing non-small cell lung cancer

OBJECTIVES

Non-small cell lung cancer (NSCLC) accounts for more than 80 % of all lung cancers, and its 5-year survival rate can be greatly improved by early diagnosis. However, early diagnosis remains elusive because of the lack of effective biomarkers. In this study, we aimed to develop an effective diagnostic model for NSCLC based on a combination of circulating biomarkers.

METHODS

Tissue-deregulated long noncoding RNAs (lncRNAs) in NSCLC were identified in datasets retrieved from the Gene Expression Omnibus (GEO, n=727) and The Cancer Genome Atlas (TCGA, n=1,135) databases, and their differential expression was verified in paired local plasma and exosome samples from NSCLC patients. Subsequently, LASSO regression was used to screen for biomarkers in a large clinical population, and a logistic regression model was used to establish a multi-marker diagnostic model. The area under the receiver operating characteristic (ROC) curve (AUC), calibration plots, decision curve analysis (DCA), clinical impact curves, and integrated discrimination improvement (IDI) were used to evaluate the efficiency of the diagnostic model.

RESULTS

Three lncRNAs-PGM5-AS1, SFTA1P, and CTA-384D8.35 were consistently expressed in online tissue datasets, plasma, and exosomes from local patients. LASSO regression identified nine variables (Plasma CTA-384D8.35, Plasma PGM5-AS1, Exosome CTA-384D8.35, Exosome PGM5-AS1, Exosome SFTA1P, Log10CEA, Log10CA125, SCC, and NSE) in clinical samples that were eventually included in the multi-marker diagnostic model. Logistic regression analysis revealed that Plasma CTA-384D8.35, exosome SFTA1P, Log10CEA, Exosome CTA-384D8.35, SCC, and NSE were independent risk factors for NSCLC (p<0.01), and their results were visualized using a nomogram to obtain personalized prediction outcomes. The constructed diagnostic model demonstrated good NSCLC prediction ability in both the training and validation sets (AUC=0.97).

CONCLUSIONS

In summary, the constructed circulating lncRNA-based diagnostic model has good NSCLC prediction ability in clinical samples and provides a potential diagnostic tool for NSCLC.