Yingfang Tian

Brain and blood microRNA expression profiling of ischemic stroke, intracerebral hemorrhage, and kainate seizures

MicroRNAs (miRNAs) regulate gene expression and have a critical role in many biologic and pathologic processes. We hypothesized that miRNA expression profiles in injured brain (hippocampus) would show common as well as unique profiles when compared with those of blood. Adult, untouched, control rats were compared with rats with sham surgeries, ischemic strokes, brain hemorrhage (lysed blood, fresh blood, or thrombin), and kainate-induced seizures. Brain and whole-blood miRNA expression profiles were assessed 24 h later using TaqMan rodent miRNA arrays. MicroRNA response profiles were different for each condition. Many miRNAs changed more than 1.5-fold in brain and blood after each experimental manipulation, and several miRNAs were upregulated or downregulated in both brain and blood after a given injury. A few miRNAs (e.g., miR-298, miR-155, and miR-362-3p) were upregulated or downregulated more than twofold in both brain and blood after several different injuries. The results show the possible use of blood miRNAs as biomarkers for brain injury; that selected blood miRNAs may correlate with miRNA changes in the brain; and that many of the mRNAs, previously shown to be regulated in brain and blood after brain injury, are likely accounted for by changes in miRNA expression.

Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood

BackgroundGene expression studies require appropriate normalization methods. One such method uses stably expressed reference genes. Since suitable reference genes appear to be unique for each tissue, we have identified an optimal set of the most stably expressed genes in human blood that can be used for normalization.MethodsWhole-genome Affymetrix Human 2.0 Plus arrays were examined from 526 samples of males and females ages 2 to 78, including control subjects and patients with Tourette syndrome, stroke, migraine, muscular dystrophy, and autism. The top 100 most stably expressed genes with a broad range of expression levels were identified. To validate the best candidate genes, we performed quantitative RT-PCR on a subset of 10 genes (TRAP1, DECR1, FPGS, FARP1, MAPRE2, PEX16, GINS2, CRY2, CSNK1G2 and A4GALT), 4 commonly employed reference genes (GAPDH, ACTB, B2M and HMBS) and PPIB, previously reported to be stably expressed in blood. Expression stability and ranking analysis were performed using GeNorm and NormFinder algorithms.ResultsReference genes were ranked based on their expression stability and the minimum number of genes needed for nomalization as calculated using GeNorm showed that the fewest, most stably expressed genes needed for acurate normalization in RNA expression studies of human whole blood is a combination of TRAP1, FPGS, DECR1 and PPIB. We confirmed the ranking of the best candidate control genes by using an alternative algorithm (NormFinder).ConclusionThe reference genes identified in this study are stably expressed in whole blood of humans of both genders with multiple disease conditions and ages 2 to 78. Importantly, they also have different functions within cells and thus should be expressed independently of each other. These genes should be useful as normalization genes for microarray and RT-PCR whole blood studies of human physiology, metabolism and disease.

Gene Expression Profiling of Blood for the Prediction of Ischemic Stroke

Background and Purpose— A blood-based biomarker of acute ischemic stroke would be of significant value in clinical practice. This study aimed to (1) replicate in a larger cohort our previous study using gene expression profiling to predict ischemic stroke; and (2) refine prediction of ischemic stroke by including control groups relevant to ischemic stroke. Methods— Patients with ischemic stroke (n=70, 199 samples) were compared with control subjects who were healthy (n=38), had vascular risk factors (n=52), and who had myocardial infarction (n=17). Whole blood was drawn ≤3 hours, 5 hours, and 24 hours after stroke onset and from control subjects. RNA was processed on whole genome microarrays. Genes differentially expressed in ischemic stroke were identified and analyzed for predictive ability to discriminate stroke from control subjects. Results— The 29 probe sets previously reported predicted a new set of ischemic strokes with 93.5% sensitivity and 89.5% specificity. Sixty- and 46-probe sets differentiated control groups from 3-hour and 24-hour ischemic stroke samples, respectively. A 97-probe set correctly classified 86% of ischemic strokes (3 hour+24 hour), 84% of healthy subjects, 96% of vascular risk factor subjects, and 75% with myocardial infarction. Conclusions— This study replicated our previously reported gene expression profile in a larger cohort and identified additional genes that discriminate ischemic stroke from relevant control groups. This multigene approach shows potential for a point-of-care test in acute ischemic stroke.

Signatures of cardioembolic and large-vessel ischemic stroke.

The cause of stroke remains unknown or cryptogenic in many patients. We sought to determine whether gene expression signatures in blood can distinguish between cardioembolic and large‐vessel causes of stroke, and whether these profiles can predict stroke etiology in the cryptogenic group.

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.

Integrated analysis of mRNA and microRNA expression in mature neurons, neural progenitor cells and neuroblastoma cells

Mature neurons (MNs), neural progenitor cells (NPCs) and neuroblastoma cells (NBCs) are all neural-derived cells. However, MNs are unable to divide once differentiated; NPCs are able to divide a limited number of times and differentiate to normal brain cell types; whereas NBCs can divide an unlimited number of times but rarely differentiate. Here, we perform whole transcriptome (mRNA, miRNA) profiling of these cell types and compare expression levels of each cell type to the others. Integrated mRNA-miRNA functional analyses reveal that: 1) several very highly expressed genes (e.g., Robo1, Nrp1, Epha3, Unc5c, Dcc, Pak3, Limk4) and a few under-expressed miRNAs (e.g., miR-152, miR-146b, miR-339-5p) in MNs are associated with one important cellular process-axon guidance; 2) some very highly expressed mitogenic pathway genes (e.g., Map2k1, Igf1r, Rara, Runx1) and under-expressed miRNAs (e.g., miR-370, miR-9, miR-672) in NBCs are associated with cancer pathways. These results provide a library of negative mRNAmiRNA networks that are likely involved in the cellular processes of differentiation and division.

Profiles of lacunar and nonlacunar stroke

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.

Effects of Gender on Gene Expression in the Blood of Ischemic Stroke Patients

This study examined the effects of gender on RNA expression after ischemic stroke (IS). RNA obtained from blood of IS patients (n = 51; 153 samples at ≤ 3, 5, and 24 hours) and from matched controls (n = 52) were processed on Affymetrix microarrays. Analyses of covariance for stroke versus control samples were performed separately for both genders and the regulated genes for females compared with males. In all, 242, 227, and 338 male-specific genes were regulated at ≤ 3, 5, and 24 hours after IS, respectively, of which 59 were regulated at all time points. Overall, 774, 3,437, and 571 female-specific stroke genes were regulated at ≤ 3, 5, and 24 hours, respectively, of which 152 were regulated at all time points. Male-specific stroke genes were associated with integrin, integrin-liked kinase, actin, tight junction, Wnt/β-catenin, RhoA, fibroblast growth factors (FGF), granzyme, and tumor necrosis factor receptor (TNFR)2 signaling. Female-specific stroke genes were associated with p53, high-mobility group box-1, hypoxia inducible factor (HIF)1α, interleukin (IL)1, IL6, IL12, IL18, acute-phase response, T-helper, macrophage, and estrogen signaling. Cell death signaling was overrepresented in both genders, although the molecules and pathways differed. Gender affects gene expression in the blood of IS patients, which likely implies gender differences in immune, inflammatory, and cell death responses to stroke.

Distinctive RNA Expression Profiles in Blood Associated With White Matter Hyperintensities in Brain

Background and Purpose— White matter hyperintensities (WMH) are areas of high signal detected by T2 and fluid-attenuated inversion recovery sequences on brain MRI. Although associated with aging, cerebrovascular risk factors, and cognitive impairment, the pathogenesis of WMH remains unclear. Thus, RNA expression was assessed in the blood of individuals with and without extensive WMH to search for evidence of oxidative stress, inflammation, and other abnormalities described in WMH lesions in brain. Methods— Subjects included 20 with extensive WMH (WMH+), 45% of whom had Alzheimer disease, and 18 with minimal WMH (WMH−), 44% of whom had Alzheimer disease. All subjects were clinically evaluated and underwent quantitative MRI. Total RNA from whole blood was processed on human whole genome Affymetrix HU133 Plus 2.0 microarrays. RNA expression was analyzed using an analysis of covariance. Results— Two hundred forty-one genes were differentially regulated at ±1.2-fold difference (P<0.005) in subjects with WMH+ as compared to WMH−, regardless of cognitive status and 50 genes were differentially regulated with ±1.5-fold difference (P<0.005). Cluster and principal components analyses showed that the expression profiles for these genes distinguished WMH+ from WMH− subjects. Function analyses suggested that WMH-specific genes were associated with oxidative stress, inflammation, detoxification, and hormone signaling, and included genes associated with oligodendrocyte proliferation, axon repair, long-term potentiation, and neurotransmission. Conclusions— The unique RNA expression profile in blood associated with WMH is consistent with roles of systemic oxidative stress and inflammation, as well as other potential processes in the pathogenesis or consequences of WMH.

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.