Gene expression in peripheral blood differs after cardioembolic compared with large-vessel atherosclerotic stroke: biomarkers for the etiology of ischemic stroke

Decoding Molecular Mechanisms Underlying Outcomes After Ischemic Stroke Thrombectomy by RNA Sequencing of Retrieved Clots

BACKGROUND

Transcriptomic profiling has emerged as a powerful tool for exploring the molecular landscape of ischemic stroke clots and providing insights into the pathophysiological mechanisms underlying stroke progression and recovery. In this study, we aimed to investigate the relationship between stroke clot transcriptomes and stroke thrombectomy outcome, as measured by early neurological improvement (ENI) 30 (i.e., a 30% reduction in NIHSS at 24 h post-thrombectomy).

HYPOTHESIS

We hypothesized that there exist distinct clot gene expression patterns between good and poor neurological outcomes.

METHODS

Transcriptomic analysis of 32 stroke clots retrieved by mechanical thrombectomy was conducted. Transcriptome data of these clots were analyzed to identify differentially expressed genes (DEGs), defined as those with a log(fold-change) ≥ 1.5 and q < 0.05 between samples with good and poor early neurological outcomes. Gene ontology and bioinformatics analyses were performed on genes with p < 0.01 to identify enriched biological processes and Ingenuity Pathway Analysis canonical pathways. Moreover, AUC analysis assessed the predictive power of DEGs for 90-day function outcome (mRS ≤ 2) and cellular composition of clot was predicted using CIBERSORT. We also assessed whether differential enrichment of immune cell types could indicate patient survival.

RESULTS

A total of 41 DEGs were identified. Bioinformatics showed that enriched biological processes and pathways emphasized the chronic immune response and matrix metalloproteinase inhibition. Moreover, 25 of the DEGs were found to be significant predictors of 90-day mRS. These genes were indicative of monocytes enrichment and neutrophil depletion in patients with poorer outcomes.

CONCLUSION

Our study revealed a distinct gene expression pattern and dysregulated biological pathways associated with ENI. This expression pattern was also predictive of long-term outcome, suggesting a biological link between those ENIs and 90-day mRS.

A case-control comparison of acute-phase peripheral blood gene expression in participants diagnosed with minor ischaemic stroke or stroke mimics

BACKGROUND

Past studies suggest that there are changes in peripheral blood cell gene expression in response to ischaemic stroke; however, the specific changes which occur during the acute phase are poorly characterised. The current study aimed to identify peripheral blood cell genes specifically associated with the early response to ischaemic stroke using whole blood samples collected from participants diagnosed with ischaemic stroke (n = 29) or stroke mimics (n = 27) following emergency presentation to hospital. Long non-coding RNA (lncRNA), mRNA and micro-RNA (miRNA) abundance was measured by RNA-seq, and the consensusDE package was used to identify genes which were differentially expressed between groups. A sensitivity analysis excluding two participants with metastatic disease was also conducted.

RESULTS

The mean time from symptom onset to blood collection was 2.6 h. Most strokes were mild (median NIH stroke scale score 2.0). Ten mRNAs (all down-regulated in samples provided by patients experiencing ischaemic stroke) and 30 miRNAs (14 over-expressed and 16 under-expressed in participants with ischaemic stroke) were significantly different between groups in the whole cohort and sensitivity analyses. No significant over-representation of gene ontology categories by the differentially expressed genes was observed. Random forest analysis suggested a panel of differentially expressed genes (ADGRG7 and miRNAs 96, 532, 6766, 6798 and 6804) as potential ischaemic stroke biomarkers, although modelling analyses demonstrated that these genes had poor diagnostic performance.

CONCLUSIONS

This study provides evidence suggesting that the early response to minor ischaemic stroke is predominantly reflected by changes in the expression of miRNAs in peripheral blood cells. Further work in independent cohorts particularly in patients with more severe stroke is needed to validate these findings and investigate their clinical relevance.

Bioinformatic identification of hub genes Myd88 and Ccl3 and TWS-119 as a potential agent for the treatment of massive cerebral infarction

Background

Massive cerebral infarction (MCI) causes severe neurological deficits, coma and can even result in death. Here, we identified hub genes and pathways after MCI by analyzing microarray data from a murine model of ischemic stroke and identified potential therapeutic agents for the treatment of MCI.

Methods

Microarray expression profiling was performed using the GSE28731 and GSE32529 datasets from the Gene Expression Omnibus (GEO) database. Data from a sham group (n = 6 mice) and a middle cerebral artery occlusion (MCAO) group (n = 7 mice) were extracted to identify common differentially expressed genes (DEGs). After identifying gene interactions, we generated a protein-protein interaction (PPI) network with Cytoscape software. Then, the MCODE plug-in in Cytoscape was used to determine key sub-modules according to MCODE scores. Enrichment analyses were then conducted on DEGs in the key sub-modules to evaluate their biological functions. Furthermore, hub genes were identified by generating the intersections of several algorithms in the cytohubba plug-in; these genes were then verified in other datasets. Finally, we used Connectivity MAP (CMap) to identify potential agents for MCI therapy.

Results

A total of 215 common DEGs were identified and a PPI network was generated with 154 nodes and 947 edges. The most significant key sub-module had 24 nodes and 221 edges. Gene ontology (GO) analysis showed that the DEGs in this sub-module showed enrichment in inflammatory response, extracellular space and cytokine activity in terms of biological process, cellular component and molecular function, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that TNF signaling was the most enriched pathway. Myd88 and Ccl3 were identified as hub genes and TWS-119 was identified as the most potential therapeutic agent by CMap.

Conclusions

Bioinformatic analysis identified two hub genes (Myd88 and Ccl3) for ischemic injury. Further analysis identified TWS-119 as the best potential candidate for MCI therapy and that this target may be associated with TLR/MyD88 signaling.

Monocyte, neutrophil, and whole blood transcriptome dynamics following ischemic stroke

BACKGROUND

After ischemic stroke (IS), peripheral leukocytes infiltrate the damaged region and modulate the response to injury. Peripheral blood cells display distinctive gene expression signatures post-IS and these transcriptional programs reflect changes in immune responses to IS. Dissecting the temporal dynamics of gene expression after IS improves our understanding of immune and clotting responses at the molecular and cellular level that are involved in acute brain injury and may assist with time-targeted, cell-specific therapy.

METHODS

The transcriptomic profiles from peripheral monocytes, neutrophils, and whole blood from 38 ischemic stroke patients and 18 controls were analyzed with RNA-seq as a function of time and etiology after stroke. Differential expression analyses were performed at 0-24 h, 24-48 h, and >48 h following stroke.

RESULTS

Unique patterns of temporal gene expression and pathways were distinguished for monocytes, neutrophils, and whole blood with enrichment of interleukin signaling pathways for different time points and stroke etiologies. Compared to control subjects, gene expression was generally upregulated in neutrophils and generally downregulated in monocytes over all times for cardioembolic, large vessel, and small vessel strokes. Self-organizing maps identified gene clusters with similar trajectories of gene expression over time for different stroke causes and sample types. Weighted Gene Co-expression Network Analyses identified modules of co-expressed genes that significantly varied with time after stroke and included hub genes of immunoglobulin genes in whole blood.

CONCLUSIONS

Altogether, the identified genes and pathways are critical for understanding how the immune and clotting systems change over time after stroke. This study identifies potential time- and cell-specific biomarkers and treatment targets.

Blood-Based Biomarkers: A Forgotten Friend of Hyperacute Ischemic Stroke

Ischemic stroke (IS) is the second leading cause of death worldwide. Multimodal neuroimaging techniques that have significantly facilitated the diagnosis of hyperacute IS are not widely used in underdeveloped areas and community hospitals owing to drawbacks such as high cost and lack of trained operators. Moreover, these methods do not have sufficient resolution to detect changes in the brain at the cellular and molecular levels after IS onset. In contrast, blood-based biomarkers can reflect molecular and biochemical alterations in both normal and pathophysiologic processes including angiogenesis, metabolism, inflammation, oxidative stress, coagulation, thrombosis, glial activation, and neuronal and vascular injury, and can thus provide information complementary to findings from routine examinations and neuroimaging that is useful for diagnosis. In this review, we summarize the current state of knowledge on blood-based biomarkers of hyperacute IS including those associated with neuronal injury, glial activation, inflammation and oxidative stress, vascular injury and angiogenesis, coagulation and thrombosis, and metabolism as well as genetic and genomic biomarkers. Meanwhile, the blood sampling time of the biomarkers which are cited and summarized in the review is within 6 h after the onset of IS. Additionally, we also discuss the diagnostic and prognostic value of blood-based biomarkers in stroke patients, and future directions for their clinical application and development.

Distinct peripheral blood monocyte and neutrophil transcriptional programs following intracerebral hemorrhage and different etiologies of ischemic stroke

Understanding cell-specific transcriptome responses following intracerebral hemorrhage (ICH) and ischemic stroke (IS) will improve knowledge of the immune response to brain injury. Transcriptomic profiles of 141 samples from 48 subjects with ICH, different IS etiologies, and vascular risk factor controls were characterized using RNA-seq in isolated neutrophils, monocytes and whole blood. In both IS and ICH, monocyte genes were down-regulated, whereas neutrophil gene expression changes were generally up-regulated. The monocyte down-regulated response to ICH included innate, adaptive immune, dendritic, NK cell and atherosclerosis signaling. Neutrophil responses to ICH included tRNA charging, mitochondrial dysfunction, and ER stress pathways. Common monocyte and neutrophil responses to ICH included interferon signaling, neuroinflammation, death receptor signaling, and NFAT pathways. Suppressed monocyte responses to IS included interferon and dendritic cell maturation signaling, phagosome formation, and IL-15 signaling. Activated neutrophil responses to IS included oxidative phosphorylation, mTOR, BMP, growth factor signaling, and calpain proteases-mediated blood-brain barrier (BBB) dysfunction. Common monocyte and neutrophil responses to IS included JAK1, JAK3, STAT3, and thrombopoietin signaling. Cell-type and cause-specific approaches will assist the search for future IS and ICH biomarkers and treatments.

Promising Biomarker Candidates for Cardioembolic Stroke Etiology. A Brief Narrative Review and Current Opinion

Determining the cause of stroke is considered one of the main objectives in evaluating a stroke patient in clinical practice. However, ischemic stroke is a heterogeneous disorder and numerous underlying disorders are implicated in its pathogenesis. Although progress has been made in identifying individual stroke etiology, in many cases underlying mechanisms still remain elusive. Since secondary prevention strategies are tailored toward individual stroke mechanisms, patients whose stroke etiology is unknown may not receive optimal preventive treatment. Cardioembolic stroke is commonly defined as cerebral vessel occlusion by distant embolization arising from thrombus formation in the heart. It accounts for the main proportion of ischemic strokes, and its share to stroke etiology is likely to rise even further in future decades. However, it can be challenging to distinguish cardioembolism from other possible etiologies. As personalized medicine advances, stroke researchers' focus is increasingly drawn to etiology-associated biomarkers. They can provide deeper insight regarding specific stroke mechanisms and can help to unravel previously undetected pathologies. Furthermore, etiology-associated biomarkers could play an important role in guiding future stroke prevention strategies. To achieve this, broad validation of promising candidate biomarkers as well as their implementation in well-designed randomized clinical trials is necessary. This review focuses on the most-promising candidates for diagnosis of cardioembolic stroke. It discusses existing evidence for possible clinical applications of these biomarkers, addresses current challenges, and outlines future perspectives.

Blood biomarkers to detect new-onset atrial fibrillation and cardioembolism in ischemic stroke patients

BACKGROUND

Accumulating data suggest blood biomarkers could inform stroke etiology.

OBJECTIVE

The purpose of this study was to investigate the performance of multiple blood biomarkers in elucidating stroke etiology with a focus on new-onset atrial fibrillation (AF) and cardioembolism.

METHODS

Between January and December 2017, information on clinical and laboratory parameters and stroke characteristics was prospectively collected from ischemic stroke patients recruited from the National University Hospital, Singapore. Multiple blood biomarkers (N-terminal pro-brain natriuretic peptide [NT-proBNP], d-dimer, S100β, neuron-specific enolase, vitamin D, cortisol, interleukin-6, insulin, uric acid, and albumin) were measured in plasma. These variables were compared with stroke etiology and the risk of new-onset AF and cardioembolism using multivariable regression methods.

RESULTS

Of the 515 ischemic stroke patients (mean age 61 years; 71% men), 44 (8.5%) were diagnosed with new-onset AF, and 75 (14.5%) had cardioembolism. The combination of 2 laboratory parameters (total cholesterol ≤169 mg/dL; triglycerides ≤44.5 mg/dL) and 3 biomarkers (NT-proBNP ≥294 pg/mL; S100β ≥64 pg/mL; cortisol ≥471 nmol/l) identified patients with new-onset AF (negative predictive value [NPV] 90%; positive predictive value [PPV] 73%; area under curve [AUC] 85%). The combination of 2 laboratory parameters (total cholesterol ≤169 mg/dL; triglycerides ≤44.5 mg/dL) and 2 biomarkers (NT-proBNP ≥507 pg/mL; S100β ≥65 pg/mL) identified those with cardioembolism (NPV 86%; PPV 78%; AUC 87%). Adding clinical predictors did not improve the performance of these models.

CONCLUSION

Blood biomarkers could identify patients with increased likelihood of cardioembolism and direct the search for occult AF.

Acute Stroke Biomarkers: Are We There Yet?

Background: Distinguishing between stroke subtypes and knowing the time of stroke onset are critical in clinical practice. Thrombolysis and thrombectomy are very effective treatments in selected patients with acute ischemic stroke. Neuroimaging helps decide who should be treated and how they should be treated but is expensive, not always available and can have contraindications. These limitations contribute to the under use of these reperfusion therapies.

Aim: An alternative approach in acute stroke diagnosis is to identify blood biomarkers which reflect the body's response to the damage caused by the different types of stroke. Specific blood biomarkers capable of differentiating ischemic from hemorrhagic stroke and mimics, identifying large vessel occlusion and capable of predicting stroke onset time would expedite diagnosis and increase eligibility for reperfusion therapies.

Summary of Review: To date, measurements of candidate biomarkers have usually occurred beyond the time window for thrombolysis. Nevertheless, some candidate markers of brain tissue damage, particularly the highly abundant glial structural proteins like GFAP and S100β and the matrix protein MMP-9 offer promising results. Grouping of biomarkers in panels can offer additional specificity and sensitivity for ischemic stroke diagnosis. Unbiased “omics” approaches have great potential for biomarker identification because of greater gene, protein, and metabolite coverage but seem unlikely to be the detection methodology of choice because of their inherent cost.

Conclusion: To date, despite the evolution of the techniques used in their evaluation, no individual candidate or multimarker panel has proven to have adequate performance for use in an acute clinical setting where decisions about an individual patient are being made. Timing of biomarker measurement, particularly early when decision making is most important, requires urgent and systematic study.

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.

Establishing molecular signatures of stroke focusing on omic approaches: a narrative review

Stroke or 'brain attack' is considered to be the major cause of mortality and morbidity worldwide after myocardial infraction. Inspite of the years of research and clinical practice, the pathogenesis of stroke still remains incompletely understood. Omics approaches not only enable the description of a huge number of molecular platforms but also have a potential to recognize new factors associated with various complex disorders including stroke. The most significant development among all other omics technologies over the recent years has been seen by genomics which is a powerful tool for exploring the genetic architecture of stroke. Genomics has decisively established itself in stroke research and by now wealth of data has been generated providing new insights into the physiology and pathophysiology of stroke. However, the efficacy of genomic data is restricted to risk prediction only. Omics approaches not only enable the description of a huge number of molecular platforms but also have a potential to recognize new factors associated with various complex disorders including stroke. The data generated by omics technologies enables clinicians to provide detailed insight into the makeup of stroke in individual patients, which will further help in developing diagnostic procedures to direct therapies. Present review has been compiled with an aim to understand the potential of integrated omics approach to help in characterization of mechanisms leading to stroke, to predict the patient risk of getting stroke by analyzing signature biomarkers and to develop targeted therapeutic strategies.

Cardioembolic Ischemic Stroke Gene Expression Fingerprint in Blood: a Systematic Review and Verification Analysis

An accurate etiological classification is key to optimize secondary prevention after ischemic stroke, but the cause remains undetermined in one third of patients. Several studies pointed out the usefulness of circulating gene expression markers to discriminate cardioembolic (CE) strokes, mainly due to atrial fibrillation (AF), while only exploring them in small cohorts. A systematic review of studies analyzing high-throughput gene expression in blood samples to discriminate CE strokes was performed. Significantly dysregulated genes were considered as candidates, and a selection of them was validated by RT-qPCR in 100 patients with defined CE or atherothrombotic (LAA) stroke etiology. Longitudinal performance was evaluated in 12 patients at three time points. Their usefulness as biomarkers for AF was tested in 120 cryptogenic strokes and 100 individuals at high-risk for stroke. Three published studies plus three unpublished datasets were considered for candidate selection. Sixty-seven genes were found dysregulated in CE strokes. CREM, PELI1, and ZAK were verified to be up-regulated in CE vs LAA (p = 0.010, p = 0.003, p < 0.001, respectively), without changes in their expression within the first 24 h after stroke onset. The combined up-regulation of these three biomarkers increased the probability of suffering from CE stroke by 23-fold. In cryptogenic strokes with subsequent AF detection, PELI1 and CREM showed overexpression (p = 0.017, p = 0.059, respectively), whereas in high-risk asymptomatic populations, all three genes showed potential to detect AF (p = 0.007, p = 0.007, p = 0.015). The proved discriminatory capacity of these gene expression markers to detect cardioembolism even in cryptogenic strokes and asymptomatic high-risk populations might bring up their use as biomarkers.

Biomarkers Associated with Stroke Risk in Atrial Fibrillation

Background:

Atrial fibrillation (AF) is associated with an increased risk of cardioembolic stroke. The risk of cardioembolism is not adequately reduced with the administration of oral anticoagulants, since a number of patients continue to experience thromboembolic events despite receiving treatment. Therefore, identification of a circulating biomarker to identify these high-risk patients would be clinically beneficial.

Objective:

In the present article, we aim to review the available data regarding use of biomarkers to predict cardioembolic stroke in patients with AF.

Methods:

We performed a thorough search of the literature in order to analyze the biomarkers identified thus far and critically evaluate their clinical significance.

Results:

A number of biomarkers have been proposed to predict cardioembolic stroke in patients with AF. Some of them are already used in the clinical practice, such as d-dimers, troponins and brain natriuretic peptide. Novel biomarkers, such as the inflammatory growth differentiation factor-15, appear to be promising, while the role of micro-RNAs and genetics appear to be useful as well. Even though these biomarkers are associated with an increased risk for thromboembolism, they cannot accurately predict future events. In light of this, the use of a scoring system, that would incorporate both circulating biomarkers and clinical factors, might be more useful.

Conclusions:

Recent research has disclosed several biomarkers as potential predictors of cardioembolic stroke in patients with AF. However, further research is required to establish a multifactorial scoring system that will identify patients at high-risk of thromboembolism, who would benefit from more intensive treatment and monitoring.

Gender Gap and Risk Factors for Poor Stroke Outcomes: A Single Hospital-Based Prospective Cohort Study

BACKGROUND

This study intended to investigate whether etiological stroke subtypes and their corresponding major risk factors have differential effects on outcomes between genders.

PATIENTS AND METHODS

We enrolled 403 consecutive patients with first-ever acute ischemic stroke (170 women, 233 men), from a referral hospital in Taiwan over a 2-year period. Gender differences in demographics, vascular risk factors, access to health care, etiological stroke subtypes, stroke severity, and outcomes were examined. The primary outcome variable of the study was any unfavorable outcome due to acute ischemic stroke, defined as a modified Rankin Scale score of 3 or higher at 90 days after stroke. Multivariable logistic regression models were used to identify predictors of poor outcomes.

RESULTS

There were no gender disparities in baseline severity, stroke subtypes, access to health care, and medical comorbidities. Although women had poorer outcomes, female gender was not a predictor of unfavorable outcomes. Important predictors included age of 75years or older (odds ratio [OR] = 2.67; 95% confidence interval [CI], 1.46-4.90), National Institutes of Health Stroke Scale greater than or equal to 8 (OR = 8.38; 95% CI, 4.61-15.2), lack of cohabitation (OR = 2.13; 95% CI, 1.26-3.61), subtypes of cardioembolism (OR = 2.76; 95% CI, 1.29-5.93), and large-artery atherosclerosis (OR = 2.93; 95% CI, 1.47-5.85). In subgroup analyses, the gender-specific independent predictors were cardioembolism (OR = 7.42; 95% CI, 2.21-24.9) or atrial fibrillation (OR = 3.57; 95% CI, 1.31-9.74) in women, and large-artery atherosclerosis (OR = 3.35; 95% CI, 1.30-8.64) or symptomatic large-artery stenosis (OR = 3.42; 95% CI, 1.69-6.96) in men. The differential effects of these predictors according to gender were revealed by interaction tests.

CONCLUSION

Atrial fibrillation and symptomatic large-artery stenosis are predictors of poor stroke outcomes in women and men, respectively.

Deep Sequencing of Small RNAs in Blood of Patients with Brain Arteriovenous Malformations

BACKGROUND

Deregulation of circulating microRNAs (miRNAs) is always associated with development and progression of human diseases. We aimed to assess whether patients with brain arteriovenous malformations (BAVMs) possess a distinct miRNA signature compared with healthy subjects.

METHODS

Three patients with unruptured BAVMs and 3 normal control subjects were recruited as case and control groups. Peripheral blood was collected, and miRNA signature was obtained by next-generation sequencing, followed by comparative, functional, and network analyses. Quantitative reverse transcription polymerase chain reaction was performed to validate expression of specific miRNAs.

RESULTS

Deep sequencing detected 246 differentially expressed miRNAs in blood samples of patients with BAVMs compared with normal control subjects. For the top 5 miRNAs, 946 target genes were predicted, and a BAVM-specific miRNA-target gene regulatory network was constructed. Functional annotation suggested that 15 of the predicted miRNA-targeted genes were involved in vascular endothelial growth factor signaling, in which 3 critical miRNAs were involved: miR-7-5p, miR-199a-5p, and miR-200b-3p.

CONCLUSIONS

We explored the miRNA expression signature of BAVMs, which will provide an important foundation for future studies on the regulation of miRNAs involved in BAVMs.

Discovery and Longitudinal Evaluation of Candidate Biomarkers for Ischaemic Stroke by Mass Spectrometry-Based Proteomics

Application of acute therapies such as thrombolysis for ischaemic stroke (IS) is constrained because of diagnostic uncertainty and the dynamic nature of stroke biology. To investigate changes in blood proteins after stroke and as a result of thrombolysis treatment we performed label-free quantitative proteomics on serum samples using high-resolution mass spectrometry and long high-performance liquid chromatography gradient (5 hours) combined with a 50-cm column to optimise the peptide separation. We identified (false discovery rate [FDR]: 1%) and quantified a total of 574 protein groups from a total of 92 samples from 30 patients. Ten patients were treated by thrombolysis as part of a randomised placebo-controlled trial and up to 5 samples were collected from each individual at different time points after stroke. We identified 26 proteins differently expressed by treatment group (FDR: 5%) and significant changes of expression over time for 23 proteins (FDR: 10%). Molecules such as fibrinogen and C-reactive protein showed expression profiles with a high-potential clinical utility in the acute stroke setting. Protein expression profiles vary acutely in the blood after stroke and have the potential to allow the construction of a stroke clock and to have an impact on IS treatment decision making.

Advancing stroke genomic research in the age of Trans-Omics big data science: Emerging priorities and opportunities

BACKGROUND

We systematically reviewed the genetic variants associated with stroke in genome-wide association studies (GWAS) and examined the emerging priorities and opportunities for rapidly advancing stroke research in the era of Trans-Omics science.

METHODS

Using the PRISMA guideline, we searched PubMed and NHGRI- EBI GWAS catalog for stroke studies from 2007 till May 2017.

RESULTS

We included 31 studies. The major challenge is that the few validated variants could not account for the full genetic risk of stroke and have not been translated for clinical use. None of the studies included continental Africans. Genomic study of stroke among Africans presents a unique opportunity for the discovery, validation, functional annotation, Trans-Omics study and translation of genomic determinants of stroke with implications for global populations. This is because all humans originated from Africa, a continent with a unique genomic architecture and a distinctive epidemiology of stroke; as well as substantially higher heritability and resolution of fine mapping of stroke genes.

CONCLUSION

Understanding the genomic determinants of stroke and the corresponding molecular mechanisms will revolutionize the development of a new set of precise biomarkers for stroke prediction, diagnosis and prognostic estimates as well as personalized interventions for reducing the global burden of stroke.

Protein microarray analysis identifies key cytokines associated with malignant middle cerebral artery infarction

INTRODUCTION

We aimed to explore potential cytokines involved in the malignant middle cerebral artery infarction (MMI) and elucidate their underlying regulatory mechanisms.

METHODS

We first developed a cytokine profile by Quantibody^® Human Cytokine Antibody Array7000 using serum samples from eight patients with MMI and eight patients with non-acute cerebral infarction (NACI). The differentially expressed cytokines were then identified in patients with MMI using two-tailed Student's t-test and Fisher's Exact Test compared with patients with NACI. Gene Ontology and pathway enrichment analyses were performed using DAVID. Protein-protein interaction (PPI) network was constructed based on STRING database.

RESULTS

A total of 10 differentially expressed cytokines were identified from 320 unique inflammatory cytokines in serums. Among them, four cytokines, like NCAM1 (neural cell adhesion molecule 1), IGFBP-6 (insulin-like growth factor binding protein 6), LYVE1 (lymphatic vessel endothelial hyaluronan receptor 1), and LCN2 (Lipocalin2), were up-regulated, while another six cytokines, such as TGFB1 (transforming growth factor, beta 1, also known as LAP), EGF (epidermal growth factor), PDGFA (platelet-derived growth factor alpha polypeptide), MMP-10 (matrix metallopeptidase 10), IL-27 (interleukin 27), and CCL2 (chemokine (C-C motif) receptor 2), were down-regulated. Moreover, cytokine-cytokine receptor interaction pathway was significantly enriched.

CONCLUSIONS

Our findings indicate that 10 differentially expressed cytokines, such as NCAM1, LCN2, IGFBP-6, LYVE1, MMP-10, IL-27, PDGFA, EGF, CCL2, and TGFB1 may participate in the development of MMI. Moreover, cytokine-cytokine receptor interaction pathway may be an important mechanism involved in this disease. These differentially expressed cytokines may serve as diagnostic biomarkers or drug targets for MMI.

A Pathway Proteomic Profile of Ischemic Stroke Survivors Reveals Innate Immune Dysfunction in Association with Mild Symptoms of Depression - A Pilot Study

Depression after stroke is a common occurrence, raising questions as to whether depression could be a long-term biological and immunological sequela of stroke. Early explanations for post-stroke depression (PSD) focused on the neuropsychological/psychosocial effects of stroke on mobility and quality of life. However, recent investigations have revealed imbalances of inflammatory cytokine levels in association with PSD, though to date, there is only one published proteomic pathway analysis testing this hypothesis. Thus, we examined the serum proteome of stroke patients (n = 44, mean age = 63.62 years) and correlated these with the Montgomery–Åsberg Depression Rating Scale (MADRS) scores at 3 months post-stroke. Overall, the patients presented with mild depression symptoms on the MADRS, M = 6.40 (SD = 7.42). A discovery approach utilizing label-free relative quantification was employed utilizing an LC-ESI–MS/MS coupled to a LTQ-Orbitrap Elite (Thermo-Scientific). Identified peptides were analyzed using the gene set enrichment approach on several different genomic databases that all indicated significant downregulation of the complement and coagulation systems with increasing MADRS scores. Complement and coagulation systems are traditionally thought to play a key role in the innate immune system and are established precursors to the adaptive immune system through pro-inflammatory cytokine signaling. Both systems are known to be globally affected after ischemic or hemorrhagic stroke. Thus, our results suggest that lowered complement expression in the periphery in conjunction with depressive symptoms post-stroke may be a biomarker for incomplete recovery of brain metabolic needs, homeostasis, and inflammation following ischemic stroke damage. Further proteomic investigations are now required to construct the temporal profile, leading from acute lesion damage to manifestation of depressive symptoms. Overall, the findings provide support for the involvement of inflammatory and immune mechanisms in PSD symptoms and further demonstrate the value and feasibility of the proteomic approach in stroke research.

Inflammatory and metabolic markers and short-time outcome in patients with acute ischemic stroke in relation to TOAST subtypes

The aim of this study was to evaluate the association between inflammatory and metabolic markers and short-time outcome with acute ischemic stroke subtypes. A total of 121 patients was classified according to TOAST criteria, such as large artery atherosclerosis (LAAS), lacunar infarct (LAC), cardioembolic infarct (CEI), other determined etiology (ODE), and undetermined etiology (UDE). The functional impairment was evaluated within the first eight hours of stroke and the outcome after three-month follow-up using the modified Rankin Scale. Blood samples were obtained up to 24 h of stroke. Compared with 96 controls, patients with LAAS, CEI, and LAC subtypes showed higher levels of white blood cells, high-sensitivity C-reactive protein (hsCRP), interleukin 6 (IL-6), metalloproteinase 9 (MMP-9), glucose, and iron (p < 0.05); and lower high-density lipoprotein cholesterol (HDL-C) (p < 0.0001); platelets, insulin, insulin resistance, and homocysteine were higher in LAC (p < 0.0001); ferritin was higher in LAAS (p < 0.0001); and total cholesterol (TC) was lower in LAAS and CEI (p < 0.01). When stroke subtypes were compared, insulin was higher in LAAS vs. LAC and in LAC vs. CEI (p < 0.05); and TC was lower in LAAS vs. LAC (p < 0.05). Outcome and rate of mortality after three-month were higher in LAAS vs. LAC (p < 0.001 and p = 0.0391 respectively). The results underscored the important role of the inflammatory response and metabolic changes in the pathogenesis of ischemic stroke subtypes that might be considered on the initial evaluation of stroke patients to identify those that could benefit with individualized therapeutic strategies that taken into account these markers after acute ischemic event.

Neuroinflammatory biomarkers: From stroke diagnosis and prognosis to therapy

Stroke is the third leading cause of death in industrialized countries and one of the largest causes of permanent disability worldwide. Therapeutic options to fight stroke are still limited and the only approved drug is tissue-plasminogen activator (tPA) and/or mechanical thrombectomy. Post-stroke inflammation is well known to contribute to the expansion of the ischemic lesion, whereas its resolution stimulates tissue repair and neuroregeneration processes. As inflammation highly influences susceptibility of stroke patients to overcome the disease, there is an increasing need to develop new diagnostic, prognostic and therapeutic strategies for post-stroke inflammation. This review provides a brief overview of the contribution of the inflammatory mechanisms to the pathophysiology of stroke. It specially focuses on the role of inflammatory biomarkers to help predicting stroke patients' outcome since some of those biomarkers might turn out to be targets to be therapeutically altered overcoming the urgent need for the identification of potent drugs to modulate stroke-associated inflammation. This article is part of a Special Issue entitled: Neuro Inflammation edited by Helga E. de Vries and Markus Schwaninger.

An Inflammatory Polymorphisms Risk Scoring System for the Differentiation of Ischemic Stroke Subtypes

Inflammation has been associated with atherothrombotic stroke and recently with cardioembolic stroke. Different genetic risk factors have been specifically associated with the subtypes of ischemic stroke (cardioembolic, atherothrombotic, and lacunar). However, there are no studies that have generated genetic risk scores for the different subtypes of ischemic stroke using polymorphisms associated with inflammation.

METHODS

We have analyzed 68 polymorphisms of 30 inflammatory mediator genes in 2,685 subjects: 1,987 stroke cases and 698 controls. We generated a genetic scoring system with the most significant polymorphisms weighted by the odds ratio of every polymorphism and taken into consideration the stroke subtype.

RESULTS

Three polymorphisms, rs1205 (CRP gene), rs1800779, and rs2257073 (NOS3 gene), were associated with cardioembolic stroke (p value <0.05). The score generated was only associated with the cardioembolic stroke subtype (p value: 0.001) and was replicated in an independent cohort (p value: 0.017). The subjects with the highest score presented a cardioembolic stroke in 92.2% of the cases (p value: 0.002).

CONCLUSION

The genetics of inflammatory markers is more closely associated with cardioembolic strokes than with atherothrombotic or lacunar strokes. The genetic risk scoring system could be useful in the prediction and differentiation of ischemic stroke; however, it might be specific to particular ischemic stroke subtypes.

Intracerebral Hemorrhage and Ischemic Stroke of Different Etiologies Have Distinct Alternatively Spliced mRNA Profiles in the Blood: a Pilot RNA-seq Study

Whole transcriptome studies have used 3′-biased expression microarrays to study genes regulated in the blood of stroke patients. However, alternatively spliced messenger RNA isoforms have not been investigated for ischemic stroke or intracerebral hemorrhage (ICH) in animals or humans. Alternative splicing is the mechanism whereby different combinations of exons of a single gene produce distinct mRNA and protein isoforms. Here, we used RNA sequencing (RNA-seq) to determine if alternative splicing differs for ICH and cardioembolic, large vessel and lacunar causes of ischemic stroke compared to controls. RNA libraries from 20 whole blood samples were sequenced to 200 M 2 × 100 bp reads using Illumina sequencing-by-synthesis technology. Differential alternative splicing was assessed using one-way analysis of variance (ANOVA), and differential exon usage was calculated. Four hundred twelve genes displayed differential alternative splicing among the groups (false discovery rate, FDR; p < 0.05). They were involved in cellular immune response, cell death, and cell survival pathways. Distinct expression signatures based on usage of 308 exons (292 genes) differentiated the groups (p < 0.0005; fold change >|1.2|). This pilot study demonstrates that alternatively spliced genes from whole blood differ in ICH compared to ischemic stroke and differ between different ischemic stroke etiologies. These results require validation in a separate cohort.

Expression profile based gene clusters for ischemic stroke detection

In microarray studies alterations in gene expression in circulating leukocytes have shown utility for ischemic stroke diagnosis. We studied forty candidate markers identified in three gene expression profiles to (1) quantitate individual transcript expression, (2) identify transcript clusters and (3) assess the clinical diagnostic utility of the clusters identified for ischemic stroke detection. Using high throughput next generation qPCR 16 of the 40 transcripts were significantly up-regulated in stroke patients relative to control subjects (p<0.05). Six clusters of between 5 and 7 transcripts were identified that discriminated between stroke and control (p values between 1.01e-9 and 0.03). A 7 transcript cluster containing PLBD1, PYGL, BST1, DUSP1, FOS, VCAN and FCGR1A showed high accuracy for stroke classification (AUC=0.854). These results validate and improve upon the diagnostic value of transcripts identified in microarray studies for ischemic stroke. The clusters identified show promise for acute ischemic stroke detection.

Gene expression in peripheral immune cells following cardioembolic stroke is sexually dimorphic

AIMS

Epidemiological studies suggest that sex has a role in the pathogenesis of cardioembolic stroke. Since stroke is a vascular disease, identifying sexually dimorphic gene expression changes in blood leukocytes can inform on sex-specific risk factors, response and outcome biology. We aimed to examine the sexually dimorphic immune response following cardioembolic stroke by studying the differential gene expression in peripheral white blood cells.

METHODS AND RESULTS

Blood samples from patients with cardioembolic stroke were obtained at ≤3 hours (prior to treatment), 5 hours and 24 hours (after treatment) after stroke onset (n = 23; 69 samples) and compared with vascular risk factor controls without symptomatic vascular diseases (n = 23, 23 samples) (ANCOVA, false discovery rate p≤0.05, |fold change| ≥1.2). mRNA levels were measured on whole-genome Affymetrix microarrays. There were more up-regulated than down-regulated genes in both sexes, and females had more differentially expressed genes than males following cardioembolic stroke. Female gene expression was associated with cell death and survival, cell-cell signaling and inflammation. Male gene expression was associated with cellular assembly, organization and compromise. Immune response pathways were over represented at ≤3, 5 and 24 h after stroke in female subjects but only at 24 h in males. Neutrophil-specific genes were differentially expressed at 3, 5 and 24 h in females but only at 5 h and 24 h in males.

CONCLUSIONS

There are sexually dimorphic immune cell expression profiles following cardioembolic stroke. Future studies are needed to confirm the findings using qRT-PCR in an independent cohort, to determine how they relate to risk and outcome, and to compare to other causes of ischemic stroke.

Evaluation of gene expression classification studies: factors associated with classification performance

Classification methods used in microarray studies for gene expression are diverse in the way they deal with the underlying complexity of the data, as well as in the technique used to build the classification model. The MAQC II study on cancer classification problems has found that performance was affected by factors such as the classification algorithm, cross validation method, number of genes, and gene selection method. In this paper, we study the hypothesis that the disease under study significantly determines which method is optimal, and that additionally sample size, class imbalance, type of medical question (diagnostic, prognostic or treatment response), and microarray platform are potentially influential. A systematic literature review was used to extract the information from 48 published articles on non-cancer microarray classification studies. The impact of the various factors on the reported classification accuracy was analyzed through random-intercept logistic regression. The type of medical question and method of cross validation dominated the explained variation in accuracy among studies, followed by disease category and microarray platform. In total, 42% of the between study variation was explained by all the study specific and problem specific factors that we studied together.

Gene expression profiling of blood in brain arteriovenous malformation patients

Brain arteriovenous malformations (BAVMs) are an important cause of intracranial hemorrhage (ICH) in young adults. Gene expression profiling of blood has led to the identification of stroke biomarkers, and may help identify BAVM biomarkers and illuminate BAVM pathogenesis. It is unknown whether blood gene expression profiles differ between 1) BAVM patients and healthy controls, or 2) unruptured and ruptured BAVM patients at presentation. We characterized blood transcriptional profiles in 60 subjects (20 unruptured BAVM, 20 ruptured BAVM, and 20 healthy controls) using Affymetrix whole genome expression arrays. Expression differences between groups were tested by ANOVA, adjusting for potential confounders. Genes with absolute fold change ≥ 1.2 (false discovery rate corrected p ≤ 0.1) were selected as differentially expressed and evaluated for over-representation in KEGG biological pathways (p ≤ 0.05). Twenty-nine genes were differentially expressed between unruptured BAVM patients and controls, including 13 which may be predictive of BAVM. Patients with ruptured BAVM compared to unruptured BAVM differed in expression of 1490 genes, with over-representation of genes in 8 pathways including MAPK, VEGF, Wnt signaling and several inflammatory pathways. These results suggest clues to the pathogenesis of BAVM and/or BAVM rupture and point to potential biomarkers or new treatment targets.

Gender-dependent correlations of carotid intima-media thickness with gene expression in blood

The mechanisms underlying gender differences in stroke incidence, risk, and outcome are uncertain. We sought to determine whether transcriptional profiles of circulating blood cells of men and women differentially correlated with carotid artery intima-media thickness (CIMT), a predictor of atherosclerosis and stroke risk. Gene expression in whole blood was measured using Affymetrix expression arrays in men (n=17) and women (n=35), aged 45-64 years, with at least one risk factor for stroke. Mean average CIMT was measured using B-mode ultrasound. Expression levels of 746 genes positively and 292 genes negatively correlated with CIMT only in women (p<0.05); 881 genes positively and 597 genes negatively correlated with CIMT only in men (p<0.05). Forty-one genes correlated with CIMT in men and women, but in opposite directions. These genes were associated with estrogen, cholesterol and lipid metabolism, inflammation, coagulation, and vasoreactivity. This pilot study provides the first proof of principle that gene expression in blood cells correlates with CIMT. These results point to potential pathophysiological mechanisms underlying sex differences in stroke risk. Since the sample size is small, the findings are preliminary and need to be confirmed in independent, larger studies.

Ischemic stroke biomarkers in blood

Ischemic stroke is a leading cause of adult disability and mortality. With over 15 million strokes occurring every year in the world, methods to better identify patients at risk for stroke are needed, as are methods to improve patient diagnosis and prognosis when stroke occurs. Use of blood-based biomarkers is one method that has been evaluated to predict risk of stroke, diagnose stroke and its causes, predict stroke severity and outcome, and guide prevention therapy. Markers that have been identified include a variety of proteins, nucleic acids and lipids that relate to stroke pathophysiology. The role of blood biomarkers in ischemic stroke is still being defined, and further study is needed to develop blood biomarkers for clinical stroke use. In this review, the authors provide a summary of biomarkers that have been divided by their potential clinical application.

Blood microRNAs in low or no risk ischemic stroke patients

Ischemic stroke is a multi-factorial disease where some patients present themselves with little or no risk factors. Blood microRNA expression profiles are becoming useful in the diagnosis and prognosis of human diseases. We therefore investigated the blood microRNA profiles in young stroke patients who presented with minimal or absence of risk factors for stroke such as type 2 diabetes, dyslipidemia and hypertension. Blood microRNA profiles from these patients varied with stroke subtypes as well as different functional outcomes (based on modified Rankin Score). These microRNAs have been shown to target genes that are involved in stroke pathogenesis. The findings from our study suggest that molecular mechanisms in stroke pathogenesis involving low or no risk ischemic stroke patients could differ substantially from those with pre-existing risk factors.

TTC7B emerges as a novel risk factor for ischemic stroke through the convergence of several genome-wide approaches

We hereby propose a novel approach to the identification of ischemic stroke (IS) susceptibility genes that involves converging data from several unbiased genetic and genomic tools. We tested the association between IS and genes differentially expressed between cases and controls, then determined which data mapped to previously reported linkage peaks and were nominally associated with stroke in published genome-wide association studies. We first performed gene expression profiling in peripheral blood mononuclear cells of 20 IS cases and 20 controls. Sixteen differentially expressed genes mapped to reported whole-genome linkage peaks, including the TTC7B gene, which has been associated with major cardiovascular disease. At the TTC7B locus, 46 tagging polymorphisms were tested for association in 565 Portuguese IS cases and 520 controls. Markers nominally associated in at least one test and defining associated haplotypes were then examined in 570 IS Spanish cases and 390 controls. Several polymorphisms and haplotypes in the intron 5-intron 6 region of TTC7B were also associated with IS risk in the Spanish and combined data sets. Multiple independent lines of evidence therefore support the role of TTC7B in stroke susceptibility, but further work is warranted to identify the exact risk variant and its pathogenic potential.

Blood Biomarkers in Stroke: Research and Clinical Practice

Blood biomarkers may have applications in stroke diagnosis, outcome prediction, or treatment. In this article, we provide a focused review on some of the methodological challenges and potential developments of biomarkers in stroke. We review the approaches to the development of a diagnostic blood marker: a candidate marker approach, marker panels, and –omics. Then we examined the role of blood markers to predict recurrent stroke and treatment response in stroke.

Blood biomarkers in cardioembolic stroke

One promising field in neurovascular diseases investigation is the use of biomarkers to guide stroke etiology diagnosis and classification. Since treatment differs among etiologic subtypes and nowadays many patients receive a diagnosis of undetermined stroke, biomarkers might become an important additional diagnostic tool. In this review we update current knowledge about biomarkers related with cardioembolic stroke etiology (such as BNP and D-dimer proteins, or PITX2 and ZFHX3 genes), that in the future, might allow rapidly guiding other diagnostic tests and accelerating the onset of an optimal secondary prevention.

Transient ischemic attacks characterized by RNA profiles in blood

OBJECTIVE

Transient ischemic attacks (TIA) are common. Though systemic inflammation and thrombosis are associated with TIA, further study may provide insight into TIA pathophysiology and possibly lead to the development of treatments specifically targeted to TIA. We sought to determine whether gene expression profiles in blood could better characterize the proinflammatory and procoagulant states in TIA patients.

METHODS

RNA expression in blood of TIA patients (n = 26) was compared to vascular risk factor control subjects without symptomatic cardiovascular disease (n = 26) using Affymetrix U133 Plus 2.0 microarrays. Differentially expressed genes in TIA were identified by analysis of covariance and evaluated with cross-validation and functional analyses.

RESULTS

Patients with TIA had different patterns of gene expression compared to controls. There were 480 probe sets, corresponding to 449 genes, differentially expressed between TIA and controls (false discovery rate correction for multiple comparisons, p ≤ 0.05, absolute fold change ≥1.2). These genes were associated with systemic inflammation, platelet activation, and prothrombin activation. Hierarchical cluster analysis of the identified genes suggested the presence of 2 patterns of RNA expression in patients with TIA. Prediction analysis identified a set of 34 genes that discriminated TIA from controls with 100% sensitivity and 100% specificity.

CONCLUSION

Patients with recent TIA have differences of gene expression in blood compared to controls. The 2 gene expression profiles associated with TIA suggests heterogeneous responses between subjects with TIA that may provide insight into cause, risk of stroke, and other TIA pathophysiology.

RNA expression profiles from blood for the diagnosis of stroke and its causes

A blood test to detect stroke and its causes would be particularly useful in babies, young children, and patients in intensive care units and for emergencies when imaging is difficult to obtain or is unavailable. Whole genome microarrays were used to show specific gene expression profiles in rats 24 hours after ischemic and hemorrhagic stroke, hypoxia, and hypoglycemia. These proof-of-principle studies revealed that groups of genes (called gene profiles) can distinguish ischemic stroke patients from controls within 3 to 24 hours after the strokes. In addition, gene expression profiles have been developed that distinguish stroke due to large-vessel atherosclerosis from cardioembolic stroke. These profiles will be useful for predicting the causes of cryptogenic stroke. The results in adults suggest that similar diagnostic tools could be developed for children.

Inflammatory and neuroendocrine biomarkers of prognosis after ischemic stroke

Stroke is the third leading cause of mortality in the USA and one of the leading causes of severe morbidity. It is important to provide stroke patients and physicians with the most accurate prognostic information to optimize care and allocation of healthcare resources. Reliable prognostic markers available during the initial phase after acute stroke may aid clinical decision-making. Several interesting candidate biomarkers have been studied to address prognostic questions; this article will focus on selected inflammatory and neuroendocrine markers. The utility of a biomarker is defined by its ability to improve clinical decision-making and add timely information beyond that readily available from clinical examination and routine imaging. This aim has not been completely achieved yet for any biomarkers, but promising data are available and further studies are ongoing.

Genetics of common polygenic ischaemic stroke: current understanding and future challenges

Stroke is the third commonest cause of death and the major cause of adult neurological disability worldwide. While much is known about conventional risk factors such as hypertension, diabetes and incidence of smoking, these environmental factors only account for a proportion of stroke risk. Up to 50% of stroke risk can be attributed to genetic risk factors, although to date no single risk allele has been convincingly identified as contributing to this risk. Advances in the field of genetics, most notably genome wide association studies (GWAS), have revealed genetic risks in other cardiovascular disease and these techniques are now being applied to ischaemic stroke. This paper covers previous genetic studies in stroke including candidate gene studies, discusses the genome wide association approach, and future techniques such as next generation sequencing and the post-GWAS era. The review also considers the overlap from other cardiovascular diseases and whether findings from these may also be informative in ischaemic stroke.

Profiles of lacunar and nonlacunar stroke

OBJECTIVE

Determining which small deep infarcts (SDIs) are of lacunar, arterial, or cardioembolic etiology is challenging, but important in delivering optimal stroke prevention therapy. We sought to distinguish lacunar from nonlacunar causes of SDIs using a gene expression profile.

METHODS

A total of 184 ischemic strokes were analyzed. Lacunar stroke was defined as a lacunar syndrome with infarction <15mm in a region supplied by penetrating arteries. RNA from blood was processed on whole genome microarrays. Genes differentially expressed between lacunar (n = 30) and nonlacunar strokes (n = 86) were identified (false discovery rate ≤ 0.05, fold change >|1.5|) and used to develop a prediction model. The model was evaluated by cross-validation and in a second test cohort (n = 36). The etiology of SDIs of unclear cause (SDIs ≥ 15mm or SDIs with potential embolic source) (n = 32) was predicted using the derived model.

RESULTS

A 41-gene profile discriminated lacunar from nonlacunar stroke with >90% sensitivity and specificity. Of the 32 SDIs of unclear cause, 15 were predicted to be lacunar, and 17 were predicted to be nonlacunar. The identified profile represents differences in immune response between lacunar and nonlacunar stroke.

INTERPRETATION

Profiles of differentially expressed genes can distinguish lacunar from nonlacunar stroke. SDIs of unclear cause were frequently predicted to be of nonlacunar etiology, suggesting that comprehensive workup of SDIs is important to identify potential cardioembolic and arterial causes. Further study is required to evaluate the gene profile in an independent cohort and determine the clinical and treatment implications of SDIs of predicted nonlacunar etiology.

Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors

Background

Transgenic mouse tumor models have the advantage of facilitating controlled in vivo oncogenic perturbations in a common genetic background. This provides an idealized context for generating transcriptome-based diagnostic models while minimizing the inherent noisiness of high-throughput technologies. However, the question remains whether models developed in such a setting are suitable prototypes for useful human diagnostics. We show that latent factor modeling of the peripheral blood transcriptome in a mouse model of breast cancer provides the basis for using computational methods to link a mouse model to a prototype human diagnostic based on a common underlying biological response to the presence of a tumor.

Methods

We used gene expression data from mouse peripheral blood cell (PBC) samples to identify significantly differentially expressed genes using supervised classification and sparse ANOVA. We employed these transcriptome data as the starting point for developing a breast tumor predictor from human peripheral blood mononuclear cells (PBMCs) by using a factor modeling approach.

Results

The predictor distinguished breast cancer patients from healthy individuals in a cohort of patients independent from that used to build the factors and train the model with 89% sensitivity, 100% specificity and an area under the curve (AUC) of 0.97 using Youden's J-statistic to objectively select the model's classification threshold. Both permutation testing of the model and evaluating the model strategy by swapping the training and validation sets highlight its stability.

Conclusions

We describe a human breast tumor predictor based on the gene expression of mouse PBCs. This strategy overcomes many of the limitations of earlier studies by using the model system to reduce noise and identify transcripts associated with the presence of a breast tumor over other potentially confounding factors. Our results serve as a proof-of-concept for using an animal model to develop a blood-based diagnostic, and it establishes an experimental framework for identifying predictors of solid tumors, not only in the context of breast cancer, but also in other types of cancer.

Molecular markers and mechanisms of stroke: RNA studies of blood in animals and humans

Whole genome expression microarrays can be used to study gene expression in blood, which comes in part from leukocytes, immature platelets, and red blood cells. Since these cells are important in the pathogenesis of stroke, RNA provides an index of these cellular responses to stroke. Our studies in rats have shown specific gene expression changes 24  hours after ischemic stroke, hemorrhage, status epilepticus, hypoxia, hypoglycemia, global ischemia, and following brief focal ischemia that simulated transient ischemic attacks in humans. Human studies show gene expression changes following ischemic stroke. These gene profiles predict a second cohort with >90% sensitivity and specificity. Gene profiles for ischemic stroke caused by large-vessel atherosclerosis and cardioembolism have been described that predict a second cohort with >85% sensitivity and specificity. Atherosclerotic genes were associated with clotting, platelets, and monocytes, and cardioembolic genes were associated with inflammation, infection, and neutrophils. These gene profiles predicted the cause of stroke in 58% of cryptogenic patients. These studies will provide diagnostic, prognostic, and therapeutic markers, and will advance our understanding of stroke in humans. New techniques to measure all coding and noncoding RNAs along with alternatively spliced transcripts will markedly advance molecular studies of human stroke.

Blood biomarkers of ischemic stroke

This review provides a summary of the protein and RNA biomarkers that have been studied for the diagnosis and assessment of ischemic stroke. Many of the biomarkers identified relate to the pathophysiology of ischemic stroke, including ischemia of CNS tissue, acute thrombosis and inflammatory response. These biomarkers are summarized by their intended clinical application in ischemic stroke including diagnosis, prediction of stroke severity and outcome, and stratification of patients for stroke therapy. Among the biomarkers discussed are recent whole genome studies using RNA expression profiles to diagnose ischemic stroke and stroke etiology. Though many candidate blood based biomarkers for ischemic stroke have been identified, none are currently used in clinical practice. With further well designed study and careful validation, the development of blood biomarkers to improve the care of patients with ischemic stroke may be achieved.

Transcriptional profiling to identify biomarkers of disease and drug response

The discovery, biological qualification and analytical validation of genomic biomarkers requires extensive collaborations between individuals with expertise in biology, statistics, bioinformatics, chemistry, clinical medicine, regulatory science and so on. For clinical utility, blood-borne biomarkers (e.g., mRNA and miRNA) of organ damage, drug toxicity and/or response would be preferred to those that are tissue based. Currently used biomarkers such as serum creatinine (indicating renal dysfunction) denote organ damage whether caused by disease, physical injury or drugs. Therefore, it is anticipated that studies of disease will discover biomarkers that can also be used to identify drug-induced injury and vice versa. This article describes transcriptomic blood-borne biomarkers that have been reported to be connected with disease and drug toxicity. Much more qualification and validation needs to be carried out before many of these biomarkers can prove useful. Discussed here are some of the lessons learned and roadblocks to success.

Exon expression and alternatively spliced genes in Tourette Syndrome

Tourette Syndrome (TS) is diagnosed based upon clinical criteria including motor and vocal tics. We hypothesized that differences in exon expression and splicing might be useful for pathophysiology and diagnosis. To demonstrate exon expression and alternatively spliced gene differences in blood of individuals with TS compared to healthy controls (HC), RNA was isolated from the blood of 26 un-medicated TS subjects and 23 HC. Each sample was run on Affymetrix Human Exon 1.0 ST (HuExon) arrays and on 3' biased U133 Plus 2.0 (HuU133) arrays. To investigate the differentially expressed exons and transcripts, analyses of covariance (ANCOVA) were performed, controlling for age, gender, and batch. Differential alternative splicing patterns between TS and HC were identified using analyses of variance (ANOVA) models in Partek. Three hundred and seventy-six exon probe sets were differentially expressed between TS and HC (raw P < 0.005, fold change >|1.2|) that separated TS and HC subjects using hierarchical clustering and Principal Components Analysis. The probe sets predicted TS compared to HC with a >90% sensitivity and specificity using a 10-fold cross-validation. Ninety genes (transcripts) had differential expression of a single exon (raw P < 0.005) and were predicted to be alternatively spliced (raw P < 0.05) in TS compared to HC. These preliminary findings might provide insight into the pathophysiology of TS and potentially provide prognostic and diagnostic biomarkers. However, the findings are tempered by the small sample size and multiple comparisons and require confirmation using PCR or deep RNA sequencing and a much larger patient population.

Brain arteriovenous malformation pathogenesis: a response-to-injury paradigm

Brain arteriovenous malformations (AVMs) are a rare but important cause of intracranial hemorrhage (ICH) in young adults. In this paper, we review both human and animal studies of brain AVM, focusing on the: (1) natural history of AVM hemorrhage, (2) genetic and expression studies of AVM susceptibility and hemorrhage, and (3) strategies for development of a brain AVM model in adult mice. These data target various mechanisms that must act in concert to regulate normal angiogenic response to injury. Based on the various lines of evidence reviewed in this paper, we propose a "response-to-injury" model of brain AVM pathogenesis.