Donor white blood cell differential is the single largest determinant of whole blood gene expression patterns.

It has become widely accepted that sample cellular composition is a significant determinant of the gene expression patterns observed in any transcriptomic experiment performed with bulk tissue. Despite this, many investigations currently performed with whole blood do not experimentally account for possible inter-specimen differences in cellularity, and often assume that any observed gene expression differences are a result of true differences in nuclear transcription. In order to determine how confounding of an assumption this may be, in this study, we recruited a large cohort of human donors (n = 138) and used a combination of next generation sequencing and flow cytometry to quantify and compare the underlying contributions of variance in leukocyte counts versus variance in other biological factors to overall variance in whole blood transcript levels. Our results suggest that the combination of donor neutrophil and lymphocyte counts alone are the primary determinants of whole blood transcript levels for up to 75% of the protein-coding genes expressed in peripheral circulation, whereas the other factors such as age, sex, race, ethnicity, and common disease states have comparatively minimal influence. Broadly, this infers that a majority of gene expression differences observed in experiments performed with whole blood are driven by latent differences in leukocyte counts, and that cell count heterogeneity must be accounted for to meaningfully biologically interpret the results.

Large-scale informatic analysis to algorithmically identify blood biomarkers of neurological damage.

The identification of precision blood biomarkers which can accurately indicate damage to brain tissue could yield molecular diagnostics with the potential to improve how we detect and treat neurological pathologies. However, a majority of candidate blood biomarkers for neurological damage that are studied today are proteins which were arbitrarily proposed several decades before the advent of high-throughput omic techniques, and it is unclear whether they represent the best possible targets relative to the remainder of the human proteome. Here, we leveraged mRNA expression data generated from nearly 12,000 human specimens to algorithmically evaluate over 17,000 protein-coding genes in terms of their potential to produce blood biomarkers for neurological damage based on their expression profiles both across the body and within the brain. The circulating levels of proteins associated with the top-ranked genes were then measured in blood sampled from a diverse cohort of patients diagnosed with a variety of acute and chronic neurological disorders, including ischemic stroke, hemorrhagic stroke, traumatic brain injury, Alzheimer's disease, and multiple sclerosis, and evaluated for their diagnostic performance. Our analysis identifies several previously unexplored candidate blood biomarkers of neurological damage with possible clinical utility, many of which whose presence in blood is likely linked to specific cell-level pathologic processes. Furthermore, our findings also suggest that many frequently cited previously proposed blood biomarkers exhibit expression profiles which could limit their diagnostic efficacy.

Use of deep artificial neural networks to identify stroke during triage via subtle changes in circulating cell counts.

BACKGROUND: The development of tools that could help emergency department clinicians recognize stroke during triage could reduce treatment delays and improve patient outcomes. Growing evidence suggests that stroke is associated with several changes in circulating cell counts. The aim of this study was to determine whether machine-learning can be used to identify stroke in the emergency department using data available from a routine complete blood count with differential. METHODS: Red blood cell, platelet, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts were assessed in admission blood samples collected from 160 stroke patients and 116 stroke mimics recruited from three geographically distinct clinical sites, and an ensemble artificial neural network model was developed and tested for its ability to discriminate between groups. RESULTS: Several modest but statistically significant differences were observed in cell counts between stroke patients and stroke mimics. The counts of no single cell population alone were adequate to discriminate between groups with high levels of accuracy; however, combined classification using the neural network model resulted in a dramatic and statistically significant improvement in diagnostic performance according to receiver-operating characteristic analysis. Furthermore, the neural network model displayed superior performance as a triage decision making tool compared to symptom-based tools such as the Cincinnati Prehospital Stroke Scale (CPSS) and the National Institutes of Health Stroke Scale (NIHSS) when assessed using decision curve analysis. CONCLUSIONS: Our results suggest that algorithmic analysis of commonly collected hematology data using machine-learning could potentially be used to help emergency department clinicians make better-informed triage decisions in situations where advanced imaging techniques or neurological expertise are not immediately available, or even to electronically flag patients in which stroke should be considered as a diagnosis as part of an automated stroke alert system.

Bioinformatic analysis of brain-specific miRNAs for identification of candidate traumatic brain injury blood biomarkers.

BACKGROUND: Detection of brain-specific miRNAs in the peripheral blood could serve as a surrogate marker of traumatic brain injury (TBI). Here, we systematically identified brain-enriched miRNAs, and tested their utility as TBI biomarkers in the acute phase of care. METHODS: Publically available microarray data generated from 29 postmortem human tissues were used to rank 1,364 miRNAs in terms of their degree of brain-specific expression. Levels of the top six ranked miRNAs were then prospectively measured in serum samples collected from 10 Patients with TBI at hospital admission, as well as from 10 controls. RESULTS: The top six miRNAs identified in our analysis (miR-124-3p, miR-219a-5p, miR-9-5p, miR-9-3p, miR-137, and miR-128-3p) were enriched 70 to 320-fold in brain relative to other tissues, and exhibited dramatically greater brain specificity compared to several miRNAs previously proposed as biomarkers. Furthermore, their levels were elevated in serum from patients with TBI compared to controls, and could collectively discriminate between groups with 90% sensitivity and 100% specificity. Interestingly, subsequent informatic pathway analysis revealed that their target transcripts were enriched for components of signaling pathways active in peripheral organs involved in common post-TBI complications. CONCLUSIONS: The six candidate miRNAs identified in this preliminary study have promise as blood biomarkers of TBI, and could also be molecular contributors to systemic physiologic changes commonly observed post-injury.

High-throughput profiling of the circulating proteome suggests sexually dimorphic corticosteroid signaling following ischemic stroke.

Increasing evidence suggests that there are innate differences between sexes with respect to stroke pathophysiology; however, the molecular mechanisms underlying these differences remain unclear. In this investigation, we employed a shotgun approach to broadly profile sex-associated differences in the plasma proteomes of a small group of male ( n = 6) and female ( n = 4) ischemic stroke patients. Peripheral blood was sampled during the acute phase of care, and liquid chromatography electrospray ionization mass spectrometry was used to quantify plasma proteins. We observed widespread differences in plasma composition, as 77 out of 294 detected proteins were significantly differentially expressed between sexes. Corticosteroid-binding globulin (CBG), a negative acute-phase reactant that inversely regulates levels of bioactive free cortisol, was the most dramatically differentially regulated, exhibiting 16-fold higher abundance in plasma from women relative to men. Furthermore, functional annotation analysis revealed that the remaining differentially expressed proteins were significantly enriched for those involved in response to corticosteroid signaling. Plasma CBG levels were further examined in an additional group of male ( n = 19) and female ( n = 28) ischemic stroke patients, as well as a group of male ( n = 13) and female ( n = 18) neurologically normal controls. CBG levels were significantly reduced in male stroke patients relative to male controls; however, no differences were observed between female stroke patients and female controls, suggesting that women may exhibit an attenuated cortisol response to stroke. Collectively, our findings reinforce the idea that there are sex-associated differences in stroke pathophysiology and suggest that cortisol signaling should be investigated further as a potential molecular mediator.

Circulating leucocytes perpetuate stroke-induced aortic dysfunction.

NEW FINDINGS: What is the central question of this study? Does a stroke event influence aortic endothelial function; and what is the role of peripheral circulating leucocytes in stroke on the vascular reactivity of the aorta? What is the main finding and its importance? In vitro co-culture experiments demonstrated that aortic endothelium-dependent relaxation was impaired when rat aortic rings were co-cultured with leucocytes stimulated with serum from stroke patients. Impaired vascular reactivity was not observed in aortic rings without leucocytes stimulated with serum from stroke patients or age-matched control patients with or without leucocytes. These data suggest that leucocyte-dependent altered aortic endothelium-dependent relaxation with stroke and the systemic consequences of stroke on vascular inflammation may occur in the aorta. Post-stroke inflammation has been linked to poor stroke outcomes. The vascular endothelium senses and responds to circulating factors, in particular inflammatory cytokines. Although stroke-associated local cerebrovascular dysfunction is well reported, the effects of a stroke on conduit artery function are not fully understood. We tested the hypothesis that serum from stroke patients triggers leucocyte-dependent aortic endothelial dysfunction that is associated with elevated concentrations of cytokines. Total leucocytes were isolated from healthy individuals, and the cells were incubated in serum from control subjects or stroke patients for 6 h. The quantity of cytokines in media was determined using an immunoassay. Vascular reactivity was determined by the rat aortic rings that were co-cultured with or without leucocytes and stimulated with serum samples from control subjects or stroke patients. Endothelium-dependent dilatation was significantly impaired in aortic rings co-cultured with leucocytes plus serum from stroke patients (50 ± 30 versus 85 ± 13%, P < 0.05) versus serum from control subjects. In contrast, no difference was observed in aortic function stimulated with serum from control subjects or stroke patients without total leucocytes. Likewise, total leucocyte-derived cytokine concentrations were significantly increased in a time-dependent manner on stimulation with serum from stroke patients (P < 0.05). These observations support the concept that the increased response of leucocytes drives the development of stroke-associated vascular endothelial dysfunction. As such, pharmacologically targeting the source of inflammatory cytokines might alleviate stroke-associated peripheral vascular dysfunction.

Circulating extracellular DNA levels are acutely elevated in ischaemic stroke and associated with innate immune system activation.

OBJECTIVE: The objective of this work was to assess the ability of peripheral blood cell-free DNA (cfDNA) levels to identify ischaemic stroke early in the acute phase of care, as well as to examine the relationship between peripheral blood cfDNA levels and stroke-induced innate immune system activation. METHODS: Upon emergency department admission, peripheral blood samples were obtained from 43 patients experiencing acute ischaemic stroke and 20 patients identified as stroke mimics. Plasma cfDNA levels were measured using quantitative polymerase chain reaction (qPCR), infarct volume and NIH stroke scale (NIHSS) were used to assess injury severity, and peripheral blood neutrophil count was used as a measure of innate immune system status. RESULTS: Peripheral blood cfDNA levels were significantly elevated in patients suffering stroke relative to those diagnosed as stroke mimics, and could differentiate between groups with 86% (95% CI = 72-95%) sensitivity and 75% (95% CI = 51-91%) specificity. Furthermore, cfDNA levels displayed significant positive associations between both infarct volume and peripheral blood neutrophil count within the stroke group. CONCLUSIONS: These findings suggest that assessment of peripheral blood cfDNA levels may be useful for the identification of ischaemic stroke in the acute care setting, and provide associative evidence that cfDNA is a potential activator of the peripheral innate immune system in response to cerebral ischaemia.

Interleukin-15 directly stimulates pro-oxidative gene expression in skeletal muscle in-vitro via a mechanism that requires interleukin-15 receptor alpha.

Interleukin-15 (IL-15) signaling is heavily regulated by a high specificity IL-15 binding protein known as interleukin-15 receptor alpha (IL-15Rα). In-vivo disruption of IL-15Rα in the constitutive IL-15Rα knock-out (IL-15RαKO) mouse results in a shift towards an oxidative muscle phenotype characterized by dramatic increases in mitochondrial density. The IL-15RαKO mouse displays elevated levels of IL-15 transcript in muscle tissue, along with increased circulating levels of IL-15. As a result, it has been suggested that loss of IL-15Rα from skeletal muscle enhances muscle IL-15 secretion, and that muscle-derived IL-15 acts in an autocrine fashion to elicit pro-oxidative effects. However, this proposed mechanism of IL-15/IL-15Rα action in skeletal muscle is based primarily on in-vivo associative observations, and has yet to be explored in a direct manner. Thus, our purpose was to assess the immediate influence of IL-15Rα on the capacity of skeletal muscle to secrete and respond to IL-15, and also to determine whether IL-15 has the ability to act directly on skeletal muscle to induce pro-oxidative changes. These aims were addressed in-vitro using primary myogenic cultures derived from IL-15RαKO mice and B6129 controls, as well as cultures of the C2C12 immortalized myogenic cell line. Cultures obtained from IL-15RαKO mice displayed a diminished capacity to secrete IL-15 in relation to B6129 controls. Acute treatment of B6129-derived cultures with recombinant IL-15 increased transcriptional expression of the pro-oxidative genes PGC1α and PPARδ. IL-15 treatment failed to elicit a similar response in cultures generated from IL-15RαKO mice. Chronic treatment of C2C12 cultures with IL-15 during myogenic differentiation resulted in mature myocytes with greater mitochondrial density in relation to vehicle treated controls. Collectively, these results provide evidence that IL-15 has the capacity to act directly on skeletal muscle in a pro-oxidative manner, and that disruption of IL-15Rα ablates the ability of skeletal muscle to secrete and respond to IL-15.

Dataset including whole blood gene expression profiles and matched leukocyte counts with utility for benchmarking cellular deconvolution pipelines.

OBJECTIVES: Cellular deconvolution is a valuable computational process that can infer the cellular composition of heterogeneous tissue samples from bulk RNA-sequencing data. Benchmark testing is a crucial step in the development and evaluation of new cellular deconvolution algorithms, and also plays a key role in the process of building and optimizing deconvolution pipelines for specific experimental applications. However, few in vivo benchmarking datasets exist, particularly for whole blood, which is the single most profiled human tissue. Here, we describe a unique dataset containing whole blood gene expression profiles and matched circulating leukocyte counts from a large cohort of human donors with utility for benchmarking cellular deconvolution pipelines. DATA DESCRIPTION: To produce this dataset, venous whole blood was sampled from 138 total donors recruited at an academic medical center. Genome-wide expression profiling was subsequently performed via next-generation RNA sequencing, and white blood cell differentials were collected in parallel using flow cytometry. The resultant final dataset contains donor-level expression data for over 45,000 protein coding and non-protein coding genes, as well as matched neutrophil, lymphocyte, monocyte, and eosinophil counts.

Brain Expression Levels of Commonly Measured Blood Biomarkers of Neurological Damage Differ with Respect to Sex, Race, and Age.

It is increasingly evident that blood biomarkers have potential to improve the diagnosis and management of both acute and chronic neurological conditions. The most well-studied candidates, and arguably those with the broadest utility, are proteins that are highly enriched in neural tissues and released into circulation upon cellular damage. It is currently unknown how the brain expression levels of these proteins is influenced by demographic factors such as sex, race, and age. Given that source tissue abundance is likely a key determinant of the levels observed in the blood during neurological pathology, understanding such influences is important in terms of identifying potential clinical scenarios that could produce diagnostic bias. In this study, we leveraged existing mRNA sequencing data originating from 2,642 normal brain specimens harvested from 382 human donors to examine potential demographic variability in the expression levels of genes which code for 28 candidate blood biomarkers of neurological damage. Existing mass spectrometry data originating from 26 additional normal brain specimens harvested from 26 separate human donors was subsequently used to tentatively assess whether observed transcriptional variance was likely to produce corresponding variance in terms of protein abundance. Genes associated with several well-studied or emerging candidate biomarkers including neurofilament light chain (NfL), ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCH-L1), neuron-specific enolase (NSE), and synaptosomal-associated protein 25 (SNAP-25) exhibited significant differences in expression with respect to sex, race, and age. In many instances, these differences in brain expression align well with and provide a mechanistic explanation for previously reported differences in blood levels.

Variability in donor leukocyte counts confound the use of common RNA sequencing data normalization strategies in transcriptomic biomarker studies performed with whole blood.

Gene expression data generated from whole blood via next generation sequencing is frequently used in studies aimed at identifying mRNA-based biomarker panels with utility for diagnosis or monitoring of human disease. These investigations often employ data normalization techniques more typically used for analysis of data originating from solid tissues, which largely operate under the general assumption that specimens have similar transcriptome composition. However, this assumption may be violated when working with data generated from whole blood, which is more cellularly dynamic, leading to potential confounds. In this study, we used next generation sequencing in combination with flow cytometry to assess the influence of donor leukocyte counts on the transcriptional composition of whole blood specimens sampled from a cohort of 138 human subjects, and then subsequently examined the effect of four frequently used data normalization approaches on our ability to detect inter-specimen biological variance, using the flow cytometry data to benchmark each specimens true cellular and molecular identity. Whole blood samples originating from donors with differing leukocyte counts exhibited dramatic differences in both genome-wide distributions of transcript abundance and gene-level expression patterns. Consequently, three of the normalization strategies we tested, including median ratio (MRN), trimmed mean of m-values (TMM), and quantile normalization, noticeably masked the true biological structure of the data and impaired our ability to detect true interspecimen differences in mRNA levels. The only strategy that improved our ability to detect true biological variance was simple scaling of read counts by sequencing depth, which unlike the aforementioned approaches, makes no assumptions regarding transcriptome composition.

Newly-identified blood biomarkers of neurological damage are correlated with infarct volume in patients with acute ischemic stroke.

Our group recently performed a genome-wide informatic analysis that highlighted eight brain-enriched proteins with strong potential to serve as blood biomarkers of neurological injury (GFAP, MBP, ß-synuclein, OPALIN, MT-3, SNAP-25, KIF5A, MOBP), including six that have yet to be widely investigated. In this study, our aim was to determine whether the circulating levels of these proteins could be used to approximate the extent of neural tissue damage in ischemic stroke. To address this aim, blood was collected from 43 ischemic stroke patients immediately upon hospital admission. The serum levels of the eight candidate proteins were measured via ELISA, infarct volume was assessed via manual tracing of neuroradiological images, and correlational analysis was performed to examine potential associative relationships. The serum levels of all eight proteins exhibited positive correlations with infarct volume, however the strongest associations were observed in a subset of four proteins known to originate from neurons specifically (MT-3, SNAP-25, KIF5A, ß-synuclein). Combining the serum levels of these neuron-originating proteins using principal components analysis produced a single composite value that was more strongly correlated with infarct volume than the levels of any single protein considered in isolation (r = 0.48, p < 0.001). Measures of these proteins could potentially be used to provide a minimally invasive approximation of lesion size when advanced imaging techniques are not available, or when imaging results are inconclusive.

Optimized methodology for product recovery following emulsion PCR: applications for amplification of aptamer libraries and other complex templates.

Bias and background issues make efficient amplification of complex template mixes such as aptamer and genomic DNA libraries via conventional PCR methods difficult; emulsion PCR is being increasingly used in such scenarios to circumvent these problems. However, before products generated via emulsion PCR can be used in downstream workflows, they need to be recovered from the water-in-oil emulsion. Often, emulsions are broken following amplification using volatile organic solvents, and product is subsequently isolated via precipitation. Unfortunately, the use of such solvents requires the implementation of special environmental controls, and the yield and purity of DNA isolated by precipitation can be highly variable. Here, we describe the optimization of a simple protocol which can be used to recover products following emulsion PCR using a 2-butanol extraction and subsequent DNA isolation via a commercially available clean-up kit. This protocol avoids the use of volatile solvents and precipitation steps, and we demonstrate that it can be used to reliably recover DNA from water-in-oil emulsions with efficiencies as high as 90%. Furthermore, we illustrate the practical applicability of this protocol by demonstrating how it can be implemented to recover a complex random aptamer library following amplification via emulsion PCR.

Diagnosis of ischemic stroke using circulating levels of brain-specific proteins measured via high-sensitivity digital ELISA.

Limited lower detection ranges associated with traditional immunoassay techniques have prevented the use of brain-specific proteins as blood biomarkers of stroke in the acute phase of care, as these proteins are often only present in circulation at low concentrations. Digital ELISA is a newly developed technique with allows for quantification of proteins in biofluids with up to 1000 times greater sensitivity than conventional ELISA techniques. The purpose of this study was to determine whether the extended lower limits of detection associated with digital ELISA could enable the use of brain-specific proteins as blood biomarkers of ischemic stroke during triage. Blood was sampled from ischemic stroke patients (n = 14) at emergency department admission, as well as from neurologically normal controls matched in terms of risk factors for cardiovascular disease (n = 33). Plasma levels of two brain-specific axonal proteins, neurofilament light chain (NfL) and tau, were measured via digital ELISA, and receiver-operating characteristic analysis was used to determine their ability to discriminate between groups. Plasma levels of NfL and tau were both significantly elevated in stroke patients versus controls, and could respectively discriminate between groups with 92.9% sensitivity / 84.9% specificity, and 85.7% sensitivity / 54.6% specificity. Furthermore, adjustment of measured NfL and Tau levels according to the lower-limits of detection associated with commercially-available conventional ELISA assays resulted in a dramatic and statistically significant decrease in diagnostic performance. Collectively, our results suggest that the increased analytical sensitivity of digital ELISA could enable the use of brain-specific proteins as blood biomarkers of ischemic stroke during triage.

Use of high-sensitivity digital ELISA improves the diagnostic performance of circulating brain-specific proteins for detection of traumatic brain injury during triage.

Background: Historically, limited sensitivity associated with traditional immunoassay methods has prevented the use of brain-specific proteins as blood biomarkers of traumatic brain injury (TBI) during triage, as these proteins exhibit low circulating concentrations. Digital ELISA is a newly-developed technique that is up to 1000 times more sensitive than conventional ELISA methods. The purpose of this study was to determine whether the use of digital ELISA over conventional ELISA improves the performance of brain-specific proteins as blood biomarkers of TBI during triage.Methods: Blood was sampled from TBI patients (n = 13) at emergency department admission, as well as from neurologically normal controls (n = 72). Serum levels of two brain-specific proteins, neurofilament light chain (NfL) and Tau, were measured via digital ELISA. Estimated conventional ELISA measures were generated by adjusting values according to the lower limits of detection achievable with commercially available conventional ELISA assays, and receiver operating characteristic (ROC) analysis was used to compare the diagnostic performance of digital ELISA measures to estimated conventional ELISA measures in terms of their ability to discriminate between TBI patients and controls.Results: Used in combination, digital ELISA measures of NfL and Tau could discriminate between groups with 100% sensitivity and 91.7% specificity. Estimated conventional ELISA measures could only discriminate between groups with 7.7% sensitivity and 94.4% specificity. This difference in diagnostic performance was statistically significant when comparing areas under ROC curves.Conclusions: The use of digital ELISA over conventional ELISA methods improves the diagnostic performance of circulating brain-specific proteins for detection of TBI during triage.

Neuro biomarker levels measured with high-sensitivity digital ELISA differ between serum and plasma.

Aim: Digital ELISA-based assays for blood biomarkers of neurological disease are on the verge of clinical use. Here, we aimed to determine whether different preanalytical blood processing techniques influence results. Materials & methods: Concentrations of neurofilament light chain (NfL), Tau and amyloid beta (Aß) were measured in human plasma and serum specimens using digital ELISA and compared between blood products. Measured levels of NfL were highly equivalant between serum and plasma in all analyses, however, measured levels of Tau and Aß were consistently lower in serum relative to plasma. Conclusion: Tau and Aß are likely lost during clotting in serum preparations, and should be assayed in plasma to get an accurate measure of circulating levels.

High-Throughput Profiling of Circulating Antibody Signatures for Stroke Diagnosis Using Small Volumes of Whole Blood.

Accurate stroke recognition during triage can streamline care and afford patients earlier access to life-saving interventions. However, the tools currently available to clinicians for prehospital and early in-hospital identification of stroke are limited. The peripheral immune system is intricately involved in stroke pathology and thus may be targetable for the development of immunodiagnostics. In this preliminary study, we sought to determine whether the circulating antibody pool is altered early in stroke, and whether such alterations could be leveraged for diagnosis. One hundred microliters of peripheral whole blood was sampled from 19 ischemic stroke patients, 17 hemorrhagic stroke patients, and 20 stroke mimics in the acute phase of care. A custom-fabricated high-density peptide array comprising 125,000 unique probes was used to assess the binding characteristics of blood-borne antibodies, and a random forest-based approach was used to select a parsimonious set of probes with an optimal ability to discriminate between groups. The coordinate antibody binding intensities of the top 17 probes identified in our analysis displayed an ability to differentiate the total pool of stroke patients from stroke mimics with 92% sensitivity and 90% specificity, as well as detect hemorrhage with 88% sensitivity and 87% specificity, as determined using a same-set cross-validation. These preliminary findings suggest that stroke-associated alterations in the circulating antibody pool may have clinical utility for diagnosis during triage, and that such a possibility warrants further investigation.

Shifts in Leukocyte Counts Drive the Differential Expression of Transcriptional Stroke Biomarkers in Whole Blood.

Our group recently identified a panel of ten genes whose RNA expression levels in whole blood have utility for detection of stroke. The purpose of this study was to determine the mechanisms by which these genes become differentially expressed during stroke pathology. First, we assessed the transcriptional distribution of the ten genes across the peripheral immune system by measuring their expression levels on isolated neutrophils, monocytes, B-lymphocytes, CD-4+ T-lymphocytes, CD-8+ T-lymphocytes, and NK-cells generated from the blood of healthy donors (n = 3). Then, we examined the relationship between the whole-blood expression levels of the ten genes and white blood cell counts in a cohort of acute ischemic stroke patients (n = 36) and acute stroke mimics (n = 15) recruited at emergency department admission. All ten genes displayed strong patterns of lineage-specific expression in our analysis of isolated leukocytes, and their whole-blood expression levels were correlated with white blood cell differential across the total patient population, suggesting that many of them are likely differentially expressed in whole blood during stroke as an artifact of stroke-induced shifts in leukocyte counts. Specifically, factor analysis inferred that over 50% of the collective variance in their whole-blood expression levels across the patient population was driven by underlying variance in white blood cell counts alone. However, the cumulative expression levels of the ten genes displayed a superior ability to discriminate between stroke patients and stroke mimics relative to white blood cell differential, suggesting that additional less prominent factors influence their expression levels which add to their diagnostic utility. These findings not only provide insight regarding this particular panel of ten genes, but also into the results of prior stroke transcriptomics studies performed in whole blood.

Analysis of Early Stroke-induced Changes in Circulating Leukocyte Counts using Transcriptomic Deconvolution.

Growing evidence suggests that stroke alters the phenotype of the peripheral immune system; better characterization of this response could provide new insights into stroke pathophysiology. In this investigation, we employed a deconvolution approach to informatically infer the cellular composition of the circulating leukocyte pool at multiple timepoints following stroke onset based on whole blood mRNA expression. Microarray data generated from the peripheral blood of 23 cardiovascular disease controls and 23 ischemic stroke patients at 3, 5, and 24 hours post-symptom onset were obtained from a public repository. Transcriptomic deconvolution was used to estimate the relative counts of nine leukocyte populations based on the expression of cell-specific transcripts, and cell counts were compared between groups across timepoints. Inferred counts of lymphoid cell populations including B-cells, CD4+ T-cells, CD8+ T-cells, γδ T-cells, and NK-cells were significantly lower in stroke samples relative to control samples. With respect to myeloid cell populations, inferred counts of neutrophils and monocytes were significantly higher in stroke samples compared to control samples, however inferred counts of eosinophils and dendritic cells were significantly lower. These collective differences were most dramatic in samples collected at 5 and 24 hours post-symptom onset. Findings were subsequently confirmed in a second dataset generated from an independent population of 24 controls and 39 ischemic stroke patients. Collectively, these results offer a comprehensive picture of the early stroke-induced changes to the complexion of the circulating leukocyte pool, and provide some of the first evidence that stroke triggers an acute decrease in eosinophil counts.

Stroke-associated pattern of gene expression previously identified by machine-learning is diagnostically robust in an independent patient population.

Our group recently employed genome-wide transcriptional profiling in tandem with machine-learning based analysis to identify a ten-gene pattern of differential expression in peripheral blood which may have utility for detection of stroke. The objective of this study was to assess the diagnostic capacity and temporal stability of this stroke-associated transcriptional signature in an independent patient population. Publicly available whole blood microarray data generated from 23 ischemic stroke patients at 3, 5, and 24 h post-symptom onset, as well from 23 cardiovascular disease controls, were obtained via the National Center for Biotechnology Information Gene Expression Omnibus. Expression levels of the ten candidate genes (ANTXR2, STK3, PDK4, CD163, MAL, GRAP, ID3, CTSZ, KIF1B, and PLXDC2) were extracted, compared between groups, and evaluated for their discriminatory ability at each time point. We observed a largely identical pattern of differential expression between stroke patients and controls across the ten candidate genes as reported in our prior work. Furthermore, the coordinate expression levels of the ten candidate genes were able to discriminate between stroke patients and controls with levels of sensitivity and specificity upwards of 90% across all three time points. These findings confirm the diagnostic robustness of the previously identified pattern of differential expression in an independent patient population, and further suggest that it is temporally stable over the first 24 h of stroke pathology.