Proteomic discovery and verification of serum amyloid A as a predictor marker of patients at risk of post-stroke infection: a pilot study

TMT and PRM Based Quantitative Proteomics to Explore the Protective Role and Mechanism of Iristectorin B in Stroke

Stroke is a serious disease caused by the rupture or blockage of the cerebrovascular system. Its pathogenesis is complex and involves multiple mechanisms. Iristectorin B is a natural isoflavone that has certain anti stroke effects. In this study, an in vitro stroke injury model of glyoxylate deprivation was established using PC12 cells, which was used to evaluate the anti-stroke activity of Iristectorin B in ejecta stem. The results showed that Iristectorin B, a natural isoflavone derived from Dried Shoot, significantly reduced the damage to PC12 cells caused by oxygen glucose deprivation/reoxygenation, decreased apoptosis, enhanced cell survival and reduced Ca2+, LDH and ROS levels. The results showed that Iristectorin B had a significant protective effect on Na2S2O4-injured PC12 cells, and the mechanism may be related to the protective effect of neurons in the brain. After protein extraction and various analyses were performed, a series of cutting-edge technologies were organically combined to study the quantitative proteome of each group. Differential proteins were then analyzed. According to the protein screening principle, ferroptosis-related proteins were most closely associated with stroke. The differential proteins associated with ferroptosis screened were SLC3A2, TFR1 and HMOX1, with HMOX1 being the most significantly elevated and reduced via dosing. Iristectorin B may act as a protective agent against stroke by regulating ferroptosis, and SLC3A2, TFR1 and HMOX1 may serve as potential diagnostic biomarkers for stroke, providing additional evidence to support the importance of ferroptosis in stroke.

The role of IL-23/IL-17 axis in ischemic stroke from the perspective of gut-brain axis

Bidirectional communication between central nervous system (CNS) and intestine is mediated by nerve, endocrine, immune and other pathways in gut-brain axis. Many diseases of CNS disturb the homeostasis of intestine and gut microbiota. Similarly, the dysbiosis of intestinal and gut microbiota also promotes the progression and deterioration of CNS diseases. IL-23/IL-17 axis is an important inflammatory axis which is widely involved in CNS diseases such as experimental autoimmune encephalomyelitis (EAE), multiple sclerosis (MS), and ischemic stroke (IS). Attributing to the long anatomically distances between ischemic brain and gut, previous studies on IL-23/IL-17 axis in IS are rarely focused on intestinal tissues. However, recent studies have found that IL-17⁺T cells in CNS mainly originate from intestine. The activation and migration of IL-17⁺T cells to CNS is likely to be affected by the altered intestinal homeostasis. These studies promoted the attention of IL-23/IL-17 axis and gut-brain axis. IS is difficult to treat because of its extremely complex pathological mechanism. This review mainly discusses the relationship between IL-23/IL-17 axis and IS from the perspective of gut-brain axis. By analyzing the immune pathways in gut-brain axis, the activation of IL-23/IL-17 axis, the roles of IL-23/IL-17 axis in gut, CNS and other systems after stoke, this review is expected to provide new enlightenments for the treatment strategies of IS.

Clinical performance evaluation of serum amyloid A module of Mindray BC-7500CS automated hematology analyzer

BACKGROUND

Laboratory detection of high values of serum amyloid A (SAA) is impaired by the hook effect. In response to this problem, Mindray has launched the new generation BC-7500CS automated hematology analyzer with an SAA autodilution (SAA-D) function. The present study aimed to verify the performance of the SAA module.

METHODS

Venous whole-blood specimens anticoagulated with EDTA-K2 were randomly collected from outpatients and inpatient of the Children's Hospital of Nanjing Medical University (CH). Background, repeatability, precision, linear range, intermode comparison, and interference of the SAA module of the Mindray BC-7500CS were evaluated, and the performance of the SAA-D function was verified.

RESULTS

The Mindray BC-7500CS showed an SAA background of 0.14 mg/L, well below that claimed by the manufacturer. Repeatability of SAA with standard deviation (SD) <0.6 mg/L and coefficient of variation (CV) <6%, the quality control (QC) precision was less than 8%. The measured value of the linear range was essentially consistent with the theoretical value, and the maximum measured values could reach 1932.38 mg/L. The deviation between whole-blood mode and micro-whole-blood mode was small (r=0.999), and the SAA module displayed high anti-interference ability. In addition, the measured results of specimens with high SAA concentration diluted by SAA-D were close to those after manual dilution (r=0.993).

CONCLUSIONS

The SAA module of the Mindray BC-7500CS had excellent performance, and the SAA-D function was highly accurate at measuring specimens with high SAA concentration, enabling reliable SAA detection in the laboratory and clinical practice.

Integrating serum proteomics and metabolomics to compare the common and distinct features between acute aggressive ischemic stroke (APIS) and acute non-aggressive ischemic stroke (ANPIS)

Understanding common and distinct pathophysiological features between acute progressive ischemic stroke (APIS) and acute non-progressive ischemic stroke (ANPIS) is a prerequisite to making clear the mechanism to determine the prognosis of acute ischemic stroke (AIS). Here, we recruited three independent sets of subjects, all of which included the APIS, ANPIS, and control groups. They were used for serum proteomic and metabolomic analyses, and validation of the critical pathophysiological processes and potential biomarkers of APIS, respectively. Results showed that there were both common and distinct metabolome and proteome between APIS and ANPIS. APIS and ANPIS shared basic processes of AIS in inflammation and oxidative stress response. Coagulation and lipid metabolism disorder, activation of the complement system, and inflammation may enhance with each other in the symptom worsening of APIS. The contents of serum amyloid A1 (SAA1) and S100 calcium-binding protein A9 (S100-A9) in the validation set confirmed the key pathophysiological processes indicated by omics data; they also jointly conferred a moderate value to distinguish APIS from ANPIS. Collectively, disturbance in coagulation and lipid metabolism, complement activation, and inflammation may be synergistically involved in symptom deterioration in APIS. SAA1 and S100-A9 serve as a potential biomarker panel to distinguish APIS from ANPIS. THE SIGNIFICANCE: In this study, we integrated serum proteomics and metabolomics to explore the similarities and differences in pathophysiological processes between APIS and ANPIS. The global metabolic networks have been constructed, and the crucial common pathophysiological processes and the key distinct pathophysiological features between APIS and ANPIS were investigated based on the differentially expressed proteins and metabolites (DEPs/DEMs). Furthermore, pivotal serum proteins (SAA1 and S100A9) were detected in a dependent set to validate the key pathophysiological characteristics, as well as to assess the possibility of them being used as a biomarker panel. Taken together, the multi-omics integration strategy used in this clinical study shows potential to comprehensively interpret and compare the pathophysiological processes of AIS in various conditions, as well as to screen a reliable new biomarker panel.

Proinflammatory laboratory predictors of pneumonia in ischemic stroke patients: prospective study

Background. Bacterial pneumonia is a frequent complication of ischemic stroke at the hospital stage. The search for prognostic laboratory markers of pneumonia remains an urgent task, as it will allow to individualize the approach to the treatment and rehabilitation of such patients. Aim. To investigate the prognostic significance of proteins of the acute phase of inflammation, as well as to evaluate them as early predictors of the development of pneumonia in patients with ischemic stroke. Materials and methods. The study included 302 patients in the acute period of ischemic stroke. C-reactive protein (CRP), tumor necrosis factor , interleukin-6 (IL-6), neutrophil elastase, neopterin, serum amyloid A (SAA), secreted phospholipase type 2 (sPLA2) were determined in all patients on the first day by enzyme immunoassay. Statistical data processing was carried out using SPSS and Microsoft Excel software (USA). Results. At the hospital stage, pneumonia developed in 82/302 patients (27.2%; 95% confidence interval 22.332.3%). The levels of CRP, IL-6, sPLA2, SAA and neopterin significantly differed in the presence and absence of pneumonia. Step-by-step logistic regression analysis revealed the significance of IL-6 and CRP concentrations in the prognosis of pneumonia. The threshold value of IL-6 concentration was 3.45 pg/ml (sensitivity 82.4%, specificity 66.7%). The prognostic value of a positive result (PPR) in the prognosis of pneumonia was 40%, a negative result (PNR) 92%. The threshold value of CRP was 1640 mg/l with a sensitivity of 65.8% and a specificity of 74.8%. The PPR of the threshold value of the concentration of CRP was 45%, PNR 80%. Conclusion. The measurement of the concentration of IL-6 and CRP on the first day of ischemic stroke makes it possible to identify patients with the greatest risk of pneumonia at the hospital stage. The results of the work indicate the necessity to include CRP and IL-6 in the list of mandatory laboratory tests that should be carried out for each patient with ischemic stroke on the first day from the onset of the disease.

The Role of Biomarkers in Atherothrombotic Stroke-A Systematic Review

Stroke represents the primary debilitating disease in adults and is the second-highest cause of death worldwide. Atherosclerosis, the most prevalent etiology for vascular conditions, is a continuous process that gradually creates and develops endothelial lesions known as atherosclerotic plaques. These lesions lead to the appearance of atherothrombotic stroke. In the last decades, the role of biological biomarkers has emerged as either diagnostic, prognostic, or therapeutic targets. This article aims to create a list of potential biomarkers related to atherothrombotic stroke by reviewing the currently available literature. We identified 23 biomarkers and assessed their roles as risk factors, detection markers, prognostic predictors, and therapeutic targets. The central aspect of these biomarkers is related to risk stratification, especially for patients who have not yet suffered a stroke. Other valuable data are focused on the predictive capabilities for stroke patients regarding short-term and long-term prognosis, including their influence over the acute phase treatment, such as rt-PA thrombolysis. Although the role of biomarkers is anticipated to be of extreme value in the future, they cannot yet compete with traditional stroke neuroimaging markers but could be used as additional tools for etiological diagnosis.

A Panel Comprising Serum Amyloid A, White Blood Cells and Nihss for the Triage of Patients at Low Risk of Post-Stroke Infection

Accurate and early prediction of poststroke infections is important to improve antibiotic therapy guidance and/or to avoid unnecessary antibiotic treatment. We hypothesized that the combination of blood biomarkers with clinical parameters could help to optimize risk stratification during hospitalization. In this prospective observational study, blood samples of 283 ischemic stroke patients were collected at hospital admission within 72 h from symptom onset. Among the 283 included patients, 60 developed an infection during the first five days of hospitalization. Performance predictions of blood biomarkers (Serum Amyloid-A (SAA), C-reactive protein, procalcitonin (CRP), white blood cells (WBC), creatinine) and clinical parameters (National Institutes of Health Stroke Scale (NIHSS), age, temperature) for the detection of poststroke infection were evaluated individually using receiver operating characteristics curves. Three machine learning techniques were used for creating panels: Associative Rules Mining, Decision Trees and an internal iterative-threshold based method called PanelomiX. The PanelomiX algorithm showed stable performance when applied to two representative subgroups obtained as splits of the main subgroup. The panel including SAA, WBC and NIHSS had a sensitivity of 97% and a specificity of 45% to identify patients who did not develop an infection. Therefore, it could be used at hospital admission to avoid unnecessary antibiotic (AB) treatment in around half of the patients, and consequently, to reduce AB resistance.

Stroke-induced immunosuppression: implications for the prevention and prediction of post-stroke infections

Stroke produces a powerful inflammatory cascade in the brain, but also a suppression of the peripheral immune system, which is also called stroke-induced immunosuppression (SIIS). The main processes that lead to SIIS are a shift from a lymphocyte phenotype T-helper (Th) 1 to a Th2 phenotype, a decrease of the lymphocyte counts and NK cells in the blood and spleen, and an impairment of the defense mechanisms of neutrophils and monocytes. The direct clinical consequence of SIIS in stroke patients is an increased susceptibility to stroke-associated infections, which is enhanced by clinical factors like dysphagia. Among these infections, stroke-associated pneumonia (SAP) is the one that accounts for the highest impact on stroke outcome, so research is focused on its early diagnosis and prevention. Biomarkers indicating modifications in SIIS pathways could have an important role in the early prediction of SAP, but currently, there are no individual biomarkers or panels of biomarkers that are accurate enough to be translated to clinical practice. Similarly, there is still no efficient therapy to prevent the onset of SAP, and clinical trials testing prophylactic antibiotic treatment and β-blockers have failed. However, local immunomodulation could open up a new research opportunity to find a preventive therapy for SAP. Recent studies have focused on the pulmonary immune changes that could be caused by stroke similarly to other acquired brain injuries. Some of the traits observed in animal models of stroke include lung edema and inflammation, as well as inflammation of the bronchoalveolar lavage fluid.

SAA and CRP are potential indicators in distinction and severity assessment for children with influenza

PURPOSE

The clinical values of C-reactive protein (CRP) and serum amyloid A (SAA) to distinguish non-severe from severe influenza in children are rarely reported.

METHODS

Baseline characteristics and laboratory results were collected and analyzed. Receiver operating characteristic (ROC) curve analysis was used for combined detection of indicators for children with influenza, and scatter-dot plots were used to compare the differences between non-severe and severe influenza.

RESULTS

Children with influenza B had more bronchitis and pneumonia (P < 0.05) and children with influenza A had more other serious symptoms (P = 0.015). Lymphocyte count, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), CRP, and SAA performed differently among children with influenza A and B. Joint detection of SAA and other indicators could better separate healthy children from children with influenza than single indicator detection. The CRP and SAA levels of children with severe influenza B infection and SAA levels of children with severe influenza A infection were significantly elevated compared with children with non-severe influenza (P < 0.05).

CONCLUSIONS

SAA and CRP could be potential indicators in distinction and severity assessment for children with influenza; however, age should be taken into account when using them in children with influenza B.

Risk factors for and impact of poststroke pneumonia in patients with acute ischemic stroke

Poststroke pneumonia (PSP) is a common complication of stroke and an important cause of death following stroke. However, the treatment of PSP remains inadequate due to severe impairment to the respiratory system by PSP. Thus, it is crucial to focus on preventing PSP to improve the prognosis of patients with stroke.This prospective single-center Cohort study aimed to investigate the risk factors for pulmonary infection following an ischemic stroke and identify whether PSP significantly influences the prognosis of patients after stroke.Altogether, 451 patients who were treated for acute ischemic stroke in the First Affiliated Hospital of Chongqing Medical University in China between April 2017 and April 2018 were enrolled. Clinical data from the patients from admission to 3 months after discharge were collected. PSP was the primary outcome and poor prognosis or death at 3 months following discharge was the secondary outcome observed in this study. We performed logistic regression analyses to identify the risk factors for PSP and test an association between pneumonia and poor prognosis or death after stroke.Our findings revealed the following risk factors for PSP: atrial fibrillation odds ratio (OR) = 2.884, 95% confidence intervals (CI) = 1.316-6.322), being bedridden (OR = 2.797, 95%CI = 1.322-5.921), subject to an invasive procedure (OR = 12.838, 95%CI = 6.296-26.178), massive cerebral infarction (OR = 3.994, 95%CI = 1.496-10.666), and dysphagia (OR = 2.441, 95%CI = 1.114-5.351). Pneumonia was a risk factor for poor prognosis (OR = 2.967, 95%CI = 1.273-6.915) and death (OR = 5.493, 95%CI = 1.825-16.53) after stroke.Hence, since pneumonia increases the risk of poor prognosis and death following acute ischemic stroke, preventing, and managing the risk factors for PSP may improve the prognosis and reduce the mortality after stroke.

Blood Biomarker Panels for the Early Prediction of Stroke-Associated Complications

Background Acute decompensated heart failure (ADHF) and respiratory tract infections (RTIs) are potentially life-threatening complications in patients experiencing stroke during hospitalization. We aimed to test whether blood biomarker panels might predict these complications early after admission. Methods and Results Nine hundred thirty-eight patients experiencing ischemic stroke were prospectively recruited in the Stroke-Chip study. Post-stroke complications during hospitalization were retrospectively evaluated. Blood samples were drawn within 6 hours after stroke onset, and 14 biomarkers were analyzed by immunoassays. Biomarker values were normalized using log-transformation and Z score. PanelomiX algorithm was used to select panels with the best accuracy for predicting ADHF and RTI. Logistic regression models were constructed with the clinical variables and the biomarker panels. The additional predictive value of the panels compared with the clinical model alone was evaluated by receiver operating characteristic curves. An internal validation through a 10-fold cross-validation with 3 repeats was performed. ADHF and RTI occurred in 19 (2%) and 86 (9.1%) cases, respectively. Three-biomarker panels were developed as predictors: vascular adhesion protein-1 >5.67, NT-proBNP (N-terminal pro-B-type natriuretic peptide) >4.98 and d-dimer >5.38 (sensitivity, 89.5%; specificity, 71.7%) for ADHF; and interleukin-6 >3.97, von Willebrand factor >3.67, and d-dimer >4.58 (sensitivity, 82.6%; specificity, 59.8%) for RTI. Both panels independently predicted stroke complications (panel for ADHF: odds ratio [OR] [95% CI], 10.1 [3-52.2]; panel for RTI: OR, 3.73 [1.95-7.14]) after adjustment by clinical confounders. The addition of the panel to clinical predictors significantly improved areas under the curve of the receiver operating characteristic curves in both cases. Conclusions Blood biomarkers could be useful for the early prediction of ADHF and RTI. Future studies should assess the usefulness of these panels in front of patients experiencing stroke with respiratory symptoms such as dyspnea.

SAA (Serum Amyloid A): A Novel Predictor of Stroke-Associated Infections

BACKGROUND AND PURPOSE

The aim of this study was to evaluate and independently validate SAA (serum amyloid A)-a recently discovered blood biomarker-to predict poststroke infections.

METHODS

The derivation cohort (A) was composed of 283 acute ischemic stroke patients and the independent validation cohort (B), of 367 patients. The primary outcome measure was any stroke-associated infection, defined by the criteria of the US Centers for Disease Control and Prevention, occurring during hospitalization. To determine the association of SAA levels on admission with the development of infections, logistic regression models were calculated. The discriminatory ability of SAA was assessed, by calculating the area under the receiver operating characteristic curve.

RESULTS

After adjusting for all predictors that were significantly associated with any infection in the univariate analysis, SAA remained an independent predictor in study A (adjusted odds ratio, 1.44 [95% CI, 1.16-1.79]; P=0.001) and in study B (adjusted odds ratio, 1.52 [1.05-2.22]; P=0.028). Adding SAA to the best regression model without the biomarker, the discriminatory accuracy improved from 0.76 (0.69-0.83) to 0.79 (0.72-0.86; P<0.001; likelihood ratio test) in study A. These results were externally validated in study B with an improvement in the area under the receiver operating characteristic curve, from 0.75 (0.70-0.81) to 0.76 (0.71-0.82; P<0.038).

CONCLUSIONS

Among patients with ischemic stroke, blood SAA measured on admission is a novel independent predictor of infection after stroke. SAA improved the discrimination between patients who developed an infection compared with those who did not in both derivation and validation cohorts. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00390962.

Accuracy of C-reactive protein, procalcitonin, serum amyloid A and neopterin for low-dose CT-scan confirmed pneumonia in elderly patients: A prospective cohort study

Objective

The diagnosis of pneumonia based on semiology and chest X-rays is frequently inaccurate, particularly in elderly patients. Older (C-reactive protein (CRP); procalcitonin (PCT)) or newer (Serum amyloid A (SAA); neopterin (NP)) biomarkers may increase the accuracy of pneumonia diagnosis, but data are scarce and conflicting. We assessed the accuracy of CRP, PCT, SAA, NP and the ratios CRP/NP and SAA/NP in a prospective observational cohort of elderly patients with suspected pneumonia.

Methods

We included consecutive patients more than 65 years old, with at least one respiratory symptom and one symptom or laboratory finding suggestive of infection, and a working diagnosis of pneumonia. Low-dose CT scan and comprehensive microbiological testing were done in all patients. The index tests, CRP, PCT, SAA and NP, were obtained within 24 hours. The reference diagnosis was assessed a posteriori by a panel of experts considering all available data, including patients’ outcome. We used area under the curve (AUROC) and Youden index to assess the accuracy and obtain optimal cut-off of the index tests.

Results

200 patients (median age 84 years) were included; 133 (67%) had pneumonia. AUROCs for the diagnosis of pneumonia was 0.64 (95% CI: 0.56–0.72) for CRP; 0.59 (95% CI: 0.51–0.68) for PCT; 0.60 (95% CI: 0.52–0.69) for SAA; 0.41 (95% CI: 0.32–0.49) for NP; 0.63 (95% CI: 0.55–0.71) for CRP/NP; and 0.61 (95% CI: 0.53–0.70) for SAA/NP. No cut-off resulted in satisfactory sensitivity or specificity.

Conclusions

Accuracy of traditional (CRP, PCT) and newly proposed biomarkers (SAA, NP) and ratios of CRP/NP and SAA/NP was too low to help diagnosing pneumonia in the elderly. CRP had the highest AUROC.

Clinical Trial Registration

NCT 02467092

Multilevel omics for the discovery of biomarkers and therapeutic targets for stroke

Despite many years of research, no biomarkers for stroke are available to use in clinical practice. Progress in high-throughput technologies has provided new opportunities to understand the pathophysiology of this complex disease, and these studies have generated large amounts of data and information at different molecular levels. The integration of these multi-omics data means that thousands of proteins (proteomics), genes (genomics), RNAs (transcriptomics) and metabolites (metabolomics) can be studied simultaneously, revealing interaction networks between the molecular levels. Integrated analysis of multi-omics data will provide useful insight into stroke pathogenesis, identification of therapeutic targets and biomarker discovery. In this Review, we detail current knowledge on the pathology of stroke and the current status of biomarker research in stroke. We summarize how proteomics, metabolomics, transcriptomics and genomics are all contributing to the identification of new candidate biomarkers that could be developed and used in clinical stroke management.

Preliminary study of the urinary proteome in Li and Han ethnic individuals from Hainan

Biomarkers indicate changes associated with disease. Blood is relatively stable due to the homeostatic mechanisms of the body; however, urine accumulates metabolites from changes in the body, making it a better source for early biomarker discovery. The Li ethnic group is a unique minority ethnic group that has only lived on Hainan Island for approximately 5,000 years. Studies have shown that various specific genetic variations are different between the Li and Han ethnic groups. However, whether the urinary proteome between these two ethnic groups is significantly different remains unknown. In this study, differential urinary proteins were identified in the Li and Han ethnic groups using liquid chromatography tandem mass spectrometry (LC-MS/MS). In total, 1,555 urinary proteins were identified. Twenty-five of the urinary proteins were statistically significantly different, 16 of which have been previously reported to be biomarkers of many diseases, and that these significantly different proteins were caused by ethnic differences rather than random differences. Ethnic group differences may be an influencing factor in urine proteome studies and should be considered when human urine samples are used for biomarker discovery.

Serum Amyloid A-Mediated Inflammasome Activation of Microglial Cells in Cerebral Ischemia

Serum amyloid A (SAA) proteins are acute-phase reactant associated with high-density lipoprotein (HDL) particles and increase in the plasma 1000-fold during inflammation. Recent studies have implicated SAAs in innate immunity and various disorders; however, the precise mechanism eludes us. Previous studies have shown SAAs are elevated following stroke and cerebral ischemia, and our studies demonstrated that SAA-deficient mice reduce inflammation and infarct volumes in a mouse stroke model. Our studies demonstrate that SAA increases the cytokine interleukin-1β (IL-1β), which is mediated by Nod-like receptor protein 3 (NLRP3) inflammasome, cathepsin B, and caspase-1 and may play a role in the pathogenesis of neurological disorders. SAA induced the expression of NLRP3, which mediated IL-1β induction in murine BV-2 cells and both sex primary mouse microglial cells, in a dose- and time-dependent fashion. Inhibition or KO of the NLRP3 in microglia prevented the increase in IL-1β. N-acetyl-l-cysteine and mito-TEMPO blocked the induction of IL-1β by inhibiting ROS with SAA treatment. In addition, inhibition of cathepsin B with different drugs or microglia from CatB-deficient mice attenuated inflammasome activation. Our studies suggest that the impact of SAA on inflammasome stimulation is mediated in part by the receptor for advanced glycation endproducts and Toll-like receptor proteins 2 and 4. SAA induced inflammatory cytokines and an M1 phenotype in the microglial cells while downregulating anti-inflammation M2 phenotype. These studies suggest that brain injury to can elicit a systemic inflammatory response mediated through SAA that contributes to the pathological outcomes.SIGNIFICANCE STATEMENT In the present study, serum amyloid A can induce that activation of the inflammasome in microglial cells and give rise to IL-1β release, which can further inflammation in the brain following neurological diseases. The also presents a novel target for therapeutic approaches in stroke.

Whole-Blood miRNA Sequencing Profiling for Vasospasm in Patients With Aneurysmal Subarachnoid Hemorrhage

Background and Purpose- Arterial vasospasm is a well-known delayed complication of aneurysmal subarachnoid hemorrhage (aSAH). However, no validated biomarker exists to help clinicians discriminating patients with aSAH who will develop vasospasm (VSP⁺) and identifying those who then deserve aggressive preventive therapy. We hypothesized that whole-blood miRNAs could be a source of candidate biomarkers for vasospasm. Methods- Using a next-generation sequencing approach, we performed whole-blood miRNA profiling between VSP⁺patients with aSAH and patients who did not develop vasospasm (VSP^-) in a prospective cohort of 32 patients. Profiling was performed on the admission day and 3 days before vasospasm. Results- Four hundred forty-two miRNAs were highly expressed in whole blood of patients with aSAH. Among them, hsa-miR-3177-3p demonstrated significant ( P=5.9×10^-5; P_{Bonferroni corrected}=0.03) lower levels in VSP^- compared with VSP⁺ patients. Looking for whole-blood mRNA correlates of hsa-miR-3177-3p, we observed some evidence that the decrease in hsa-miR-3177-3p levels after aSAH was associated with an increase in LDHA mRNA levels in VSP^- ( P<10^-3) but not in VSP⁺ ( P=0.66) patients. Conclusions- Whole-blood miRNA levels of hsa-miR-3177-3p could serve as a biomarker for vasospasm. Clinical Trial Registration- URL: https://www.clinicaltrials.gov . Unique identifier: NCT01779713.

Biomarkers predictive value for early diagnosis of Stroke-Associated Pneumonia

To confirm the diagnostic accuracy of candidate biomarkers in stroke-associated pneumonia (SAP), we prospectively enrolled ischemic stroke patients with NIHSS ≥ 10 on admission from March-2016 to August-2017. Blood samples were collected at baseline, 24 and 48 h after stroke onset. Biomarkers (MR-proADM, suPAR, SAA) were determined by immunoassays. Regarding biomarkers, MR-proADM at 24 h (P = 0.04) and both suPAR and SAA at 48 h (P = 0.036 and P = 0.057) were associated with pneumonia. The combination of SAA > 25.15 mg/dL and suPAR> 3.14 ng/mL at 48 h had 80% sensitivity and 95.8% specificity when both biomarkers were above the cut-off. The evaluated biomarkers represent promising tools to be evaluated in future large, prospective studies on SAP. An accurate SAP diagnosis by thorax CT might help to reduce variability in such studies.

Multiplex Assay for Quantification of Acute Phase Proteins and Immunoglobulin A in Dried Blood Spots

Inflammation is the first line defense mechanism against infection, tissue damage, or cancer development. However, inappropriate inflammatory response may also trigger diseases. The quantification of inflammatory proteins is essential to distinguish between harmful and beneficial immune response. Currently used immunoanalytical assays may suffer specificity issues due to antigen-antibody interaction and possible cross-reactivity of antibody with other protein species. In addition, immunoanalytical assays typically require invasive blood sampling and additional logistics; they are relatively costly and highly challenging to multiplex. We present a multiplex assay based on selected reaction monitoring (SRM) for quantification of seven acute-phase proteins (i.e., SAA1, SAA2-isoform1, SAA4, CRP, A1AT-isoform1, A1AG1, A1AG2) and the adaptive immunity effector IGHA1 in dried blood spots. This type of sample is readily available from all human subjects including newborns. The study utilizes proteotypic isotopically labeled peptides with trypsin-cleavable tag and presents optimized and reproducible workflow and several important practical remarks regarding quantitative SRM assays development. The panel of inflammatory proteins was quantified with sequence specificity capable to differentiate protein isoforms with intra- and interday precision (<16.4% coefficient of variation (CV) and <14.3% CV, respectively). Quantitative results were correlated with immuno-nephelometric assay (typically greater than 0.9 Pearson's R).

Combining H-FABP and GFAP increases the capacity to differentiate between CT-positive and CT-negative patients with mild traumatic brain injury

Mild traumatic brain injury (mTBI) patients may have trauma-induced brain lesions detectable using CT scans. However, most patients will be CT-negative. There is thus a need for an additional tool to detect patients at risk. Single blood biomarkers, such as S100B and GFAP, have been widely studied in mTBI patients, but to date, none seems to perform well enough. In many different diseases, combining several biomarkers into panels has become increasingly interesting for diagnoses and to enhance classification performance. The present study evaluated 13 proteins individually-H-FABP, MMP-1, MMP-3, MMP-9, VCAM, ICAM, SAA, CRP, GSTP, NKDA, PRDX1, DJ-1 and IL-10-for their capacity to differentiate between patients with and without a brain lesion according to CT results. The best performing proteins were then compared and combined with the S100B and GFAP proteins into a CT-scan triage panel. Patients diagnosed with mTBI, with a Glasgow Coma Scale score of 15 and one additional clinical symptom were enrolled at three different European sites. A blood sample was collected at hospital admission, and a CT scan was performed. Patients were divided into two two-centre cohorts and further dichotomised into CT-positive and CT-negative groups for statistical analysis. Single markers and panels were evaluated using Cohort 1. Four proteins-H-FABP, IL-10, S100B and GFAP-showed significantly higher levels in CT-positive patients. The best-performing biomarker was H-FABP, with a specificity of 32% (95% CI 23-40) and sensitivity reaching 100%. The best-performing two-marker panel for Cohort 1, subsequently validated in Cohort 2, was a combination of H-FABP and GFAP, enhancing specificity to 46% (95% CI 36-55). When adding IL-10 to this panel, specificity reached 52% (95% CI 43-61) with 100% sensitivity. These results showed that proteins combined into panels could be used to efficiently classify CT-positive and CT-negative mTBI patients.

Sepsis biomarkers reprofiling to predict stroke-associated infections

We aimed to evaluate the usefulness of sepsis biomarkers to predict stroke-associated infections. Soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), mid-regional pro-adrenomedullin (MR-proADM), presepsin (sCD14), and soluble urokinase-type plasminogen activator receptor (suPAR), were explored in 125 blood samples collected at different time-points. At baseline, MR-proADM was an independent predictor of infection [>0.94pg/mL, OR=3.63 (1.16-11.33), p=0.026], as well as suPAR at 24h [>2185.8pg/mL, OR=5.81 (1.05-32.26), p=0.044]. Both MR-proADM and suPAR were raised in patients with infections throughout the first week after stroke. These results are especially relevant for MR-proADM given its early elevation, which would allow early preventive interventions.