Salivary Xanthine Oxidase as a Potential Biomarker in Stroke Diagnostics

Salivary chemokines and growth factors in patients with ischemic stroke

Stroke is a serious health problem that affects an increasing number of people. As a result of the blockage of blood flow, tissue necrosis occurs in areas of the brain supplied by the damaged vessel, and leads to the development of inflammation. Changes that occur in the brain allow molecules to enter the blood, and it has been suggested that some can also penetrate the saliva. This study is the first to assess the profile of 25 chemokines and growth factors in the saliva of stroke survivors compared to a control group. 22 stroke survivors and 22 individuals matched by age and gender were enrolled in the study. Salivary chemokines and growth factors were assessed using the multiplex ELISA method. In the unstimulated saliva of stroke patients, we demonstrated significantly higher levels of chemotactic factors (CTACK/CCL27, IL-8/CXCL8, MIG/CXCL9, MIF) and growth factors (basic FGF, G-CSF, HGF, LIF, VEGF) compared to controls. The levels of MCP-3/CCL7, eotaxin/CCL11, IP-10/CXCL10, IL-3/MCGF, and PDGF-BB were lower in the saliva of the study group. The concentration of basic FGF negatively correlated with cognitive function as measured by the Addenbrooke's Cognitive Examination (ACE) scale (p = 0.007 r = - 0.56), while salivary IL-3 and LIF levels positively correlated with scores on the Functional Independence Measure (FIM) scale (p = 0.019 r = 0.53; p  = 0.033 r = 0.47, respectively). Receiver Operating Characteristic (ROC) analysis showed that salivary basic FGF, HGF, IL-3 and LIF can distinguish ischemic stroke patients from the control group with high sensitivity and specificity. In conclusion, disruptions in chemokine and growth factor levels in saliva may suggest an inflammatory etiology of ischemic stroke. Salivary basic FGF, HGF, IL-3 and LIF could serve as potential biomarkers for stroke. Further research is needed to illuminate the differences in salivary inflammatory mediator profiles in stroke and to evaluate the diagnostic utility of chemokines and growth factors in clinical practice.

The Effect of Xanthine Oxidase Inhibitors in the Prevention and Treatment of Stroke: A Systematic Review and Meta-Analysis

BACKGROUND

Xanthine oxidase inhibitors (XOIs) may help prevent stroke. However, heterogeneity can be found in the conclusions of different studies. The relevant evidence was summarized in this systematic review and meta-analysis to further clarify the role of XOIs in the prevention and treatment of stroke, with a focus on evaluating the effects of XOIs in primary and secondary prevention of stroke, acute stroke treatment, and reduction of post-stroke complications.

METHODS

Randomized controlled trials (RCTs) or cohort studies on the effect of XOIs in the prevention and treatment of stroke were searched in PubMed, EMBASE, and Cochrane Library from inception to 3 March 2024, along with hand searching. The analyses were carried out using Review Manager 5.4.

RESULTS

The analysis included 14 studies (115,579 patients). While XOIs did not significantly reduce the risk of stroke (RR: 0.89; 95% CI: 0.59-1.34), they improved post-stroke functional outcomes, with a reduction in the modified Rankin scale scores (mean difference: -0.6; 95% CI: -0.8 to -0.4), decreased intercellular adhesion molecule-1 levels (mean difference: -15.2 ng/mL; 95% CI: -22.3 to -8.1), improved augmentation index (AIx) by 4.2% (95% CI: 2.5-5.9%), reduced central blood pressure (mean reduction: 4.8 mmHg; 95% CI: 2.6-6.9), and delayed carotid intima-media thickness progression (mean difference: -0.05 mm/year; 95% CI: -0.08 to -0.02).

Concentration and activation biresponsive strategy in one analysis system with simultaneous use of G4 structure-specific signal probe and enzyme-catalyzed reaction

BACKGROUND

Enzymes with critical effects on life systems are regulated by expression and activation to modulate life processes. However, further insights into enzyme functions and mechanisms in various physiological processes are limited to concentration or activation analysis only. Currently, enzyme analysis has received notable attention, particularly simultaneous analysis of their concentration and activation in one system. Herein, N-methyl mesoporphyrin IX (NMM), a specific dye with notable structural selectivity for parallel G-quadruplex nucleic acid enzyme (G4h DNAzyme), is employed for the analysis of its concentration. In addition, the peroxidase activity of G4h DNAzyme is characterized based on G4h DNAzyme-catalyzed decomposition of H2O2 to continuously consume luminol. Accordingly, an increased fluorescence (FL) response of NMM and a decreased FL response of luminol could be simultaneously employed to analyze the concentration and activation of G4h DNAzyme.

RESULT

Herein, a novel concentration and activation biresponsive strategy is proposed using a G4h DNAzyme-based model that simultaneously employs a G4h structure-specific signal probe for enzyme concentration analysis and G4h DNAzyme-catalyzed reactions for enzyme activation analysis. Under optimal conditions, the biresponsive strategy can be effectively used for the simultaneous analysis of G4h DNAzyme concentration and activation, with detection limits of 718.7 pM and 233.4 nM respectively, delivering acceptable performances both in cell and in vitro.

SIGNIFICANCE

This strategy can not only be applied to concentration and activation analyses of G4h DNAzyme but can also be easily extended to other enzymes by simultaneously combining concentration analysis via target-induced direct reaction and activation analysis via target-induced catalytic reaction, offering deeper insights into various enzymes and enabling their effective implementation in bioanalysis and biochemistry.

Body fluid multiomics in 3PM-guided ischemic stroke management: health risk assessment, targeted protection against health-to-disease transition, and cost-effective personalized approach are envisaged

Because of its rapid progression and frequently poor prognosis, stroke is the third major cause of death in Europe and the first one in China. Many independent studies demonstrated sufficient space for prevention interventions in the primary care of ischemic stroke defined as the most cost-effective protection of vulnerable subpopulations against health-to-disease transition. Although several studies identified molecular patterns specific for IS in body fluids, none of these approaches has yet been incorporated into IS treatment guidelines. The advantages and disadvantages of individual body fluids are thoroughly analyzed throughout the paper. For example, multiomics based on a minimally invasive approach utilizing blood and its components is recommended for real-time monitoring, due to the particularly high level of dynamics of the blood as a body system. On the other hand, tear fluid as a more stable system is recommended for a non-invasive and patient-friendly holistic approach appropriate for health risk assessment and innovative screening programs in cost-effective IS management. This article details aspects essential to promote the practical implementation of highlighted achievements in 3PM-guided IS management.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00376-2.

Body fluids biomarkers associated with prognosis of acute ischemic stroke: progress and prospects

Acute ischemic stroke (AIS) is one of the most common strokes posing a grave threat to human life and health. Predicting the prognosis of AIS allows for an understanding of disease progress, and a better quality of life by making individualized treatment scheme. In this paper, we conducted a systematic search on PubMed, focusing on the relevant literature in the last 5 years. Summarizing the candidate prognostic biomarkers of AIS in body fluids such as blood, urine, saliva and cerebrospinal fluid is often of great significance for the management of acute ischemic stroke, which has the potential to facilitate early diagnosis, treatment, prevention and long-term outcome improvement.

Machine Learning-Based Clinical Prediction Models for Acute Ischemic Stroke Based on Serum Xanthine Oxidase Levels

OBJECTIVE

Early prediction of the onset, progression and prognosis of acute ischemic stroke (AIS) is helpful for treatment decision-making and proactive management. Although several biomarkers have been found to predict the progression and prognosis of AIS, these biomarkers have not been widely used in routine clinical practice. Xanthine oxidase (XO) is a form of xanthine oxidoreductase (XOR), which is widespread in various organs of the human body and plays an important role in redox reactions and ischemia‒reperfusion injury. Our previous studies have shown that serum XO levels on admission have certain clinical predictive value for AIS. The purpose of this study was to utilize serum XO levels and clinical data to establish machine learning models for predicting the onset, progression, and prognosis of AIS.

METHODS

We enrolled 328 consecutive patients with AIS and 107 healthy controls from October 2020 to September 2021. Serum XO levels and stroke-related clinical data were collected. We established 5 machine learning models-the logistic regression (LR), support vector machine (SVM), decision tree, random forest, and K-nearest neighbor (KNN) models-to predict the onset, progression, and prognosis of AIS. The area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, negative predictive value, and positive predictive value were used to evaluate the predictive performance of each model.

RESULTS

Among the 5 machine learning models predicting AIS onset, the AUROC values of 4 prediction models were over 0.7, while that of the KNN model was lower (AUROC = 0.6708, 95% CI 0.576-0.765). The LR model showed the best AUROC value (AUROC = 0.9586, 95% CI 0.927-0.991). Although the 5 machine learning models showed relatively poor predictive value for the progression of AIS (all AUROCs <0.7), the LR model still showed the highest AUROC value (AUROC = 0.6543, 95% CI 0.453-0.856). We compared the value of 5 machine learning models in predicting the prognosis of AIS, and the LR model showed the best predictive value (AUROC = 0.8124, 95% CI 0.715-0.910).

CONCLUSIONS

The tested machine learning models based on serum levels of XO could predict the onset and prognosis of AIS. Among the 5 machine learning models, we found that the LR model showed the best predictive performance. Machine learning algorithms improve accuracy in the early diagnosis of AIS and can be used to make treatment decisions.

A Metabolomic Signature of Ischemic Stroke Showing Acute Oxidative and Energetic Stress

Metabolomics is a powerful data-driven tool for in-depth biological phenotyping that could help identify the specific metabolic profile of cryptogenic strokes, for which no precise cause has been identified. We performed a targeted quantitative metabolomics study in West African patients who had recently suffered an ischemic stroke, which was either cryptogenic (n = 40) or had a clearly identified cause (n = 39), compared to a healthy control group (n = 40). Four hundred fifty-six metabolites were accurately measured. Multivariate analyses failed to reveal any metabolic profile discriminating between cryptogenic ischemic strokes and those with an identified cause but did show superimposable metabolic profiles in both groups, which were clearly distinct from those of healthy controls. The blood concentrations of 234 metabolites were significantly affected in stroke patients compared to controls after the Benjamini-Hochberg correction. Increased methionine sulfoxide and homocysteine concentrations, as well as an overall increase in saturation of fatty acids, were indicative of acute oxidative stress. This signature also showed alterations in energetic metabolism, cell membrane integrity, monocarbon metabolism, and neurotransmission, with reduced concentrations of several metabolites known to be neuroprotective. Overall, our results show that cryptogenic strokes are not pathophysiologically distinct from ischemic strokes of established origin, and that stroke leads to intense metabolic remodeling with marked oxidative and energetic stresses.

Temporal change of serum xanthine oxidase levels and its relation to clinical outcome of severe traumatic brain injury: a prospective cohort study

Xanthine oxidase (XO) may be involved in the induction of oxidative stress and inflammation. We measured serum XO levels at multiple days to determine whether it is associated with the severity and prognosis of severe traumatic brain injury (sTBI). In this prospective cohort study, we quantified serum XO levels in 112 sTBI patients and 112 controls. Serum XO levels of patients were measured at admission and at days 1, 3, 5, 7, and 10 after sTBI. Extended Glasgow outcome scale scores of 1-4 at post-trauma 180 days were defined as a poor prognosis. Multivariate analysis was employed to determine the relationship between poor prognosis and serum XO levels at multiple days. Serum XO levels were significantly increased at admission among patients, afterwards elevated gradually, peaked at day 3, and then diminished gradually until day 10, and were substantially higher during 10 days in patients than in controls. Serum XO levels at 6 different days were all correlated with admission Rotterdam computed tomography (CT) scores and Glasgow coma scale (GCS) scores. Serum XO levels at 6 different days were all substantially higher in patients with poor prognosis than in those with good prognosis. Serum XO levels at days 7 and 10, but not at days 1, 3, and 5, had significantly lower area under receiver operating characteristic (AUC) than those at admission. Serum XO levels at admission and at days 1 and 3, but not at day 5, were independently associated with 180-day poor prognosis. Prognostic prediction model containing GCS scores, Rotterdam CT scores, and serum XO levels at admission (or at days 1 and 3) showed substantially higher AUC than GCS scores and Rotterdam CT scores alone. The models were visually described using nomograms, which were comparatively stable under calibration curve and were relatively of clinical benefit under decision curve. Elevated serum XO levels during early period of sTBI are more closely associated with trauma severity and clinical adverse outcomes, assuming that serum XO may serve as a potential prognostic biomarker in sTBI.

Biomarkers of Cardiovascular Diseases in Saliva and Gingival Crevicular Fluid: A Review

Due to the fact that cardiovascular diseases (CVDs) have become the most serious problem in public health, there is a need for new and efficient methods for screening and early detection. In the recent literature, saliva and gingival crevicular fluid (GCF) have been gaining recognition as sources of many potential biomarkers of various systemic diseases, mainly because of correlation between the level of some compounds in the blood and saliva and association between the composition of saliva and health status. In this review, we summarize published findings of patients with atherosclerosis, arterial hypertension, coronary artery disease (CAD), acute coronary syndrome (ACS), and stroke in the context of clinical utility of saliva and GCF in diagnosing and assessing CVD severity. We hypothesize that substances in saliva including inflammatory markers, enzymes, or hormones might become novel contributors to the diagnosis and screening of CVDs. In particular, C-reactive protein (CRP), tumor necrosis alpha (TNFα), and cortisol seem to be the most promising. However, further investigation is warranted to determine the most effective markers and methods for their analysis.

Iron homeostasis imbalance and ferroptosis in brain diseases

Brain iron homeostasis is maintained through the normal function of blood-brain barrier and iron regulation at the systemic and cellular levels, which is fundamental to normal brain function. Excess iron can catalyze the generation of free radicals through Fenton reactions due to its dual redox state, thus causing oxidative stress. Numerous evidence has indicated brain diseases, especially stroke and neurodegenerative diseases, are closely related to the mechanism of iron homeostasis imbalance in the brain. For one thing, brain diseases promote brain iron accumulation. For another, iron accumulation amplifies damage to the nervous system and exacerbates patients' outcomes. In addition, iron accumulation triggers ferroptosis, a newly discovered iron-dependent type of programmed cell death, which is closely related to neurodegeneration and has received wide attention in recent years. In this context, we outline the mechanism of a normal brain iron metabolism and focus on the current mechanism of the iron homeostasis imbalance in stroke, Alzheimer's disease, and Parkinson's disease. Meanwhile, we also discuss the mechanism of ferroptosis and simultaneously enumerate the newly discovered drugs for iron chelators and ferroptosis inhibitors.

Surface-Enhanced Raman Analysis of Uric Acid and Hypoxanthine Analysis in Fractionated Bodily Fluids

In recent years, the disease burden of hyperuricemia has been increasing, especially in high-income countries and the economically developing world with a Western lifestyle. Abnormal levels of uric acid and hypoxanthine are associated with many diseases, and therefore, to demonstrate improved methods of uric acid and hypoxanthine detection, three different bodily fluids were analysed using surface-enhanced Raman spectroscopy (SERS) and high-performance liquid chromatography (HPLC). Gold nanostar suspensions were mixed with series dilutions of uric acid and hypoxanthine, 3 kDa centrifugally filtered human blood serum, urine and saliva. The results show that gold nanostars enable the quantitative detection of the concentration of uric acid and hypoxanthine in the range 5-50 μg/mL and 50-250 ng/mL, respectively. The peak areas of HPLC and maximum peak intensity of SERS have strongly correlated, notably with the peaks of uric acid and hypoxanthine at 1000 and 640 cm^-1, respectively. The r² is 0.975 and 0.959 for uric acid and hypoxanthine, respectively. Each of the three body fluids has a number of spectral features in common with uric acid and hypoxanthine. The large overlap of the spectral bands of the SERS of uric acid against three body fluids at spectra peaks were at 442, 712, 802, 1000, 1086, 1206, 1343, 1436 and 1560 cm^-1. The features at 560, 640, 803, 1206, 1290 and 1620 cm^-1 from hypoxanthine were common to serum, saliva and urine. There is no statistical difference between HPLC and SERS for determination of the concentration of uric acid and hypoxanthine (p > 0.05). For clinical applications, 3 kDa centrifugal filtration followed by SERS can be used for uric acid and hypoxanthine screening is, which can be used to reveal the subtle abnormalities enhancing the great potential of vibrational spectroscopy as an analytical tool. Our work supports the hypnosis that it is possible to obtain the specific concentration of uric acid and hypoxanthine by comparing the SER signals of serum, saliva and urine. In the future, the analysis of other biofluids can be employed to detect biomarkers for the diagnosis of systemic pathologies.

The clinical value of serum xanthine oxidase levels in patients with acute ischemic stroke

Xanthine oxidase (XO), a form of xanthine oxidoreductase, is widely distributed in various human tissues. As a major source for the generation of superoxide radicals, XO is involved in the induction of oxidative stress and inflammation during ischemic and hypoxic tissue injury. Therefore, we designed this study to identify the role of serum XO levels in acute ischemic stroke (AIS) pathogenesis. In this single-center prospective study, 328 consecutive patients with AIS for the first time were included, and 107 age- and sex-matched healthy controls from a community-based stroke screening population were also included. The serum levels of XO and several conventional stroke risk factors were assessed. Multivariate analysis was applied to evaluate the relationship between serum levels of XO and clinical outcomes, and nomogram models were developed to predict the onset, progression and prognosis of AIS. Compared with the healthy control group, the serum level of XO was significantly higher in the AIS group (P < 0.05) and was an independent risk factor for AIS (OR 8.68, 95% CI 4.62-14.33, P < 0.05). Patients with progressive stroke or a poor prognosis had a much higher serum level of XO than patients with stable stroke or a good prognosis (all P < 0.05). In addition, the serum level of XO was an independent risk factor for stroke progression (OR 1.98, 95% CI 1.12-3.50, P = 0.018) and a poor prognosis (OR 2.51, 95% CI 1.47-3.31, P = 0.001). The nomogram models including XO to predict the onset, progression and prognosis of AIS had good prediction and differentiation abilities. The findings of this study show that the serum level of XO on admission was an independent risk factor for AIS and had certain clinical predictive value for stroke progression and prognosis in patients with AIS.

Forgetful, sad and old: Do vascular cognitive impairment and depression share a common pre-disease network and how is it impacted by ageing?

Vascular cognitive impairment (VCI) and depression frequently coexist in geriatric populations and reciprocally increase disease risks. We assert that a shared pre-disease state of the psycho-immune-neuroendocrine (PINE) network model mechanistically explains bidirectional associations between VCI and depression. Five pathophysiological sub-networks are identified that are shared by VCI and depression: neuroinflammation, kynurenine pathway imbalance, hypothalamic-pituitary-adrenal (HPA) axis overactivity, impaired neurotrophic support and cerebrovascular dysfunction. These do not act independently, and their complex interactions necessitate a systems biology approach to better define disease pathogenesis. The PINE network is already established in the context of non-communicable diseases (NCDs) such as depression, hypertension, atherosclerosis, coronary heart disease and type 2 diabetes mellitus. We build on previous literature to specifically explore mechanistic links between MDD and VCI in the context of PINE pathways and discuss key mechanistic commonalities linking these comorbid conditions and identify a common pre-disease state which precedes transition to VCI and MDD. We expand the model to incorporate bidirectional interactions with biological ageing. Diathesis factors for both VCI and depression feed into this network and the culmination of shared mechanisms (on an ageing substrate) lead to a critical network transition to one or both disease states. A common pre-disease state underlying VCI and depression can provide clinicians a unique opportunity for early risk assessment and intervention in disease development. Establishing the mechanistic elements and systems biology of this network can reveal early warning or predictive biomarkers together with novel therapeutic targets. Integrative studies are recommended to elucidate the dynamic networked biology of VCI and depression over time.

Could inflammation contribute to salivary gland dysfunction in patients with chronic heart failure?

Heart failure (HF) is one of the leading causes of death worldwide. HF results not only in cardiovascular dysfunction, but also numerous pathologies in the oral cavity and salivary glands. The present study is the first to evaluate whether salivary inflammatory and anti-inflammatory factors may be related with the occurrence of hyposalivation in HF patients. We also evaluated the potential of salivary biomarkers in the diagnostics of HF. The study included 30 women with HF and 30 sex- and age-matched healthy controls. We demonstrated significantly higher levels of pro-inflammatory cytokines, anti-inflammatory cytokines, Th1, Th2, Th17, chemokines and growth factors in unstimulated saliva of HF patients compared to controls. However, the results do not indicate dominance of either branch of the immune response. The concentration of selected biomarkers is significantly higher in patients with HF and salivary gland dysfunction compared to patients with normal saliva secretion and healthy subjects (IL-1β, TNF-α, IL-7, IL-13, INF-γ, IL-12, IL-15, IL-5, IL-6, IL-9, IL-17, MCP-1/CCL-2, EOTAXIN/CCL11, RANTES/CCL5, GM-CSF, VEGF, FGF basic, PDFG-BB). Multivariate regression analysis showed that the content of salivary cytokines, chemokines and growth factors is highly dependent on salivary gland function, i.e. salivary flow rate, total protein content and amylase activity. Using receiver operating characteristic (ROC) analysis, we showed that salivary TNF-α, INF-γ, IL-12 and EOTAXIN/CCL11 differentiated patients with HF and hyposalivation with the highest sensitivity and specificity compared to patients with normal salivary secretion and controls. Interestingly, the content of some pro- and anti-inflammatory mediators in saliva significantly exceeds their concentration in plasma. In addition, salivary biomarker levels do not reflect their plasma content, which may suggest a different nature/severity of inflammatory changes at the central (blood) and local (salivary) levels. Although our study was purely observational, the significantly higher concentration of inflammatory parameters in saliva compared to plasma, as well as the lack of saliva-blood correlation, may suggest increased production/secretion of these compounds in salivary cells of HF patients. ROC analysis did not confirm the diagnostic utility of salivary cytokines and chemokines in the differential diagnosis of HF patients.

SARS-CoV-2 reliably detected in frozen saliva samples stored up to one year

Viability of saliva samples stored for longer than 28 days has not been reported in the literature. The COVID-19 pandemic has spawned new research evaluating various sample types, thus large biobanks have been started. Residual saliva samples from university student surveillance testing were retested on SalivaDirect and compared with original RT-PCR (cycle threshold values) and quantitative antigen values for each month in storage. We conclude that saliva samples stored at -80°C are still viable in detecting SARS-CoV-2 after 12 months of storage, establishing the validity of these samples for future testing.