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ABSTRACT: BACKGROUND: Inattentiveness, impulsivity and hyperactivity are the primary behaviors associated with attention-deficit hyperactivity disorder (ADHD). Previous studies showed that peripheral blood gene expression signatures can mirror central nervous system disease. Tourette syndrome (TS) is associated with inattention (IA) and hyperactivity/impulsivity (HI) symptoms over 50% of the time. This study determined if gene expression in blood correlated significantly with IA and/or HI rating scale scores in participants with TS. METHODS: RNA was isolated from the blood of 21 participants with TS, and gene expression measured on Affymetrix human U133 Plus 2.0 arrays. To identify the genes that correlated with Conners' Parents Ratings of IA and HI ratings of symptoms, an analysis of covariance (ANCOVA) was performed, controlling for age, gender and batch. RESULTS: There were 1201 gene probesets that correlated with IA scales, 1625 that correlated with HI scales, and 262 that correlated with both IA and HI scale scores (P<0.05, |Partial correlation (rp)|>0.4). Immune, catecholamine and other neurotransmitter pathways were associated with IA and HI behaviors. A number of the identified genes (n=27) have previously been reported in ADHD genetic studies. Many more genes correlated with either IA or HI scales alone compared to those that correlated with both IA and HI scales. CONCLUSIONS: These findings support the concept that the pathophysiology of ADHD and/or its subtypes in TS may involve the interaction of multiple genes. These preliminary data also suggest gene expression may be useful for studying IA and HI symptoms that relate to ADHD in TS and perhaps non-TS participants. These results will need to be confirmed in future studies.
BMC Medical Genomics 10/2012; 5(1):49. · 3.69 Impact Factor
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Joan Gunther,
Yingfang Tian,
Boryana Stamova,
Lisa Lit,
Blythe Corbett,
Brad Ander,
Xinhua Zhan,
Glen Jickling,
Netty Bos-Veneman,
Da Liu,
Pieter Hoekstra, Frank Sharp
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ABSTRACT: Tourette syndrome (TS) is a heritable disorder characterized by tics that are decreased in some patients by treatment with alpha adrenergic agonists and dopamine receptor blockers. Thus, this study examines the relationship between catecholamine gene expression in blood and tic severity. TS diagnosis was confirmed using Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria and tic severity measured using the Yale Global Tic Severity Scale (YGTSS) for 26 un-medicated subjects with TS. Whole blood was collected and Ribonucleic acid (RNA) processed on Affymetrix Human Exon 1.0 ST arrays. An Analysis of Covariance (ANCOVA) identified 3627 genes correlated with tic severity (p<0.05). Searches of Medical Subject Headings, Gene Ontology, Allen Mouse Brain Atlas, and PubMed determined genes associated with catecholamines and located in the basal ganglia. Using GeneCards, PubMed, and manual curation, seven genes associated with TS were further examined: DRD2, HRH3, MAOB, BDNF, SNAP25, SLC6A4, and SLC22A3. These genes are highly associated with TS and have also been implicated in other movement disorders, Attention Deficit Hyperactivity Disorder (ADHD), and Obsessive-Compulsive Disorder (OCD). Correlation of gene expression in peripheral blood with tic severity may allow inferences about catecholamine pathway dysfunction in TS subjects. Findings built on previous work suggest that at least some genes expressed peripherally are relevant for central nervous system (CNS) pathology in the brain of individuals with TS.
Psychiatry Research 05/2012; · 2.52 Impact Factor
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Xinhua Zhan,
Glen Jickling,
Yingfang Tian,
Boryana Stamova,
Huichin Xu,
Bradley Ander,
Renee Turner,
Matthew Mesias,
Pierro Verro,
Cheryl Bushnell,
S.Claiborne Johnston, Frank Sharp
Neurology. 01/2011; 77:1718-24.
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Glen Jickling,
Xinhua Zhan,
Bradley Ander,
Renée Turner,
Boryana Stamova,
Huichun Xu,
Yingfang Tian,
Dazhi Liu,
Ryan Davis,
Paul Lapchak, Frank Sharp
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ABSTRACT: Abstract
Background
Tissue plasminogen activator (tPA) is known to have functions beyond fibrinolysis in acute ischemic stroke, such as blood brain barrier disruption. To further delineate tPA functions in the blood, we examined the gene expression profiles induced by tPA in a rat model of ischemic stroke.
Results
tPA differentially expressed 929 genes in the blood of rats (p ≤ 0.05, fold change ≥ |1.2|). Genes identified had functions related to modulation of immune cells. tPA gene expression was found to be dependent on the reperfusion status of cerebral vasculature. The majority of genes regulated by tPA were different from genes regulated by ischemic stroke.
Conclusions
tPA modulates gene expression in the blood of rats involving immune cells in a manner that is dependent on the status of vascular reperfusion. These non-fibrinolytic activities of tPA in the blood serve to better understand tPA-related complications.
BMC Genomics. 01/2010;
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Boryana Stamova,
Peter G Green,
Yingfang Tian,
Irva Hertz-Picciotto,
Isaac N Pessah,
Robin Hansen,
Xiaowei Yang,
Jennifer Teng,
Jeffrey P Gregg,
Paul Ashwood,
Judy Van de Water, Frank R Sharp
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ABSTRACT: Gene expression in blood was correlated with mercury levels in blood of 2- to 5-year-old boys with autism (AU) compared to age-matched typically developing (TD) control boys. This was done to address the possibility that the two groups might metabolize toxicants, such as mercury, differently. RNA was isolated from blood and gene expression assessed on whole genome Affymetrix Human U133 expression microarrays. Mercury levels were measured using an inductively coupled plasma mass spectrometer. Analysis of covariance (ANCOVA) was performed and partial correlations between gene expression and mercury levels were calculated, after correcting for age and batch effects. To reduce false positives, only genes shared by the ANCOVA models were analyzed. Of the 26 genes that correlated with mercury levels in both AU and TD boys, 11 were significantly different between the groups (P(Diagnosis*Mercury) ≤ 0.05). The expression of a large number of genes (n = 316) correlated with mercury levels in TD but not in AU boys (P ≤ 0.05), the most represented biological functions being cell death and cell morphology. Expression of 189 genes correlated with mercury levels in AU but not in TD boys (P ≤ 0.05), the most represented biological functions being cell morphology, amino acid metabolism, and antigen presentation. These data and those in our companion study on correlation of gene expression and lead levels show that AU and TD children display different correlations between transcript levels and low levels of mercury and lead. These findings might suggest different genetic transcriptional programs associated with mercury in AU compared to TD children.
Neurotoxicity Research 11/2009; 19(1):31-48. · 3.51 Impact Factor
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Yingfang Tian,
Peter G Green,
Boryana Stamova,
Irva Hertz-Picciotto,
Isaac N Pessah,
Robin Hansen,
Xiaowei Yang,
Jeffrey P Gregg,
Paul Ashwood,
Glen Jickling,
Judy Van de Water, Frank R Sharp
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ABSTRACT: The objective of this study was to examine the correlation between gene expression and lead (Pb) levels in blood in children with autism (AU, n = 37) compared to typically developing controls (TD, n = 15). We postulated that, though lead levels did not differ between the groups, AU children might metabolize lead differently compared to TD children. RNA was isolated from blood and processed on Affymetrix microarrays. Separate analyses of covariance (ANCOVA) corrected for age and gender were performed for TD, AU, and all subjects (AU + TD). To reduce false positives, only genes that overlapped these three ANCOVAs were considered. Thus, 48 probe sets correlated with lead levels in both AU and TD subjects and were significantly different between the groups (p(Diagnosis x log₂Pb) < 0.05). These genes were related mainly to immune and inflammatory processes, including MHC Class II family members and CD74. A large number (n = 791) of probe sets correlated (P ≤ 0.05) with lead levels in TD but not in AU subjects; and many probe sets (n = 162) correlated (P ≤ 0.05) with lead levels in AU but not in TD subjects. Only 30 probe sets correlated (P ≤ 0.05) with lead levels in a similar manner in the AU and TD groups. These data show that AU and TD children display different associations between transcript levels and low levels of lead. We postulate that this may relate to the underlying genetic differences between the two groups, though other explanations cannot be excluded.
Neurotoxicity Research 11/2009; 19(1):1-13. · 3.51 Impact Factor
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Boryana S Stamova,
Michelle Apperson,
Wynn L Walker,
Yingfang Tian,
Huichun Xu,
Peter Adamczy,
Xinhua Zhan,
Da-Zhi Liu,
Bradley P Ander,
Isaac H Liao,
Jeffrey P Gregg,
Renee J Turner,
Glen Jickling,
Lisa Lit, Frank R Sharp
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ABSTRACT: Gene 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.
Whole-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.
Reference 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).
The 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.
BMC Medical Genomics 09/2009; 2:49. · 3.69 Impact Factor
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ABSTRACT: Autism is a syndrome with a number of etiologies with differing mechanisms that lead to abnormal development. This review highlights the need to identify autism subgroups as they each might require unique approaches for prevention or treatment.
Targeting treatments to specific mechanisms and utilizing biomarkers can more rapidly advance our understanding of how to classify and treat autism subgroups based on translational mechanisms. We illustrate this approach using mechanisms that may influence the course of autism and provide rationale for selected biomarkers that could guide treatments targeted anywhere from DNA to symptom expression.
The use of potential biomarkers that point to specific mechanisms of disordered neurodevelopment will help identify meaningful subtypes of autism and will help tailor treatment or prevention strategies for each mechanism rather than solely to a symptom category.
Medical Hypotheses 08/2009; 73(6):950-4. · 1.39 Impact Factor
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ABSTRACT: The objective of this study was to examine RNA expression in blood of subjects with Duchenne muscular dystrophy (DMD). Whole blood was collected into PAX gene tubes and RNA was isolated for 3- to 20-year-old males with DMD (n = 34) and for age- and gender-matched normal healthy controls (n = 21). DMD was confirmed by genetic testing in all subjects. RNA expression was measured on Affymetrix whole-genome human U133 Plus 2.0 GeneChips. Using a Benjamini-Hochberg false discovery rate of 0.05 to correct for multiple comparisons, an unpaired t test for DMD versus controls yielded 10,763 regulated probes with no fold change cutoff, 1,467 probes with >|1.5|-fold change, 191 probes with >|2.0|-fold change, and 59 probes with a >|2.5|-fold change. These genes (probes) separated DMD from controls using cluster analyses. Almost all of the genes regulated in peripheral blood were different from the genes reported to be regulated in diseased muscle of subjects with DMD. It is proposed that the genes regulated in blood of subjects with Duchenne muscular dystrophy are indicative, at least in part, of the immune response to the diseased DMD muscle. The regulated genes might be used to monitor therapy or provide novel targets for immune-directed therapy for DMD.
Neurogenetics 01/2009; 10(2):117-25. · 3.35 Impact Factor
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ABSTRACT: Non-biological experimental error routinely occurs in microarray data collected in different batches. It is often impossible to compare groups of samples from independent experiments because batch effects confound true gene expression differences. Existing methods can correct for batch effects only when samples from all biological groups are represented in every batch.
In this report we describe a generalized empirical Bayes approach to correct for cross-experimental batch effects, allowing direct comparisons of gene expression between biological groups from independent experiments. The proposed experimental design uses identical reference samples in each batch in every experiment. These reference samples are from the same tissue as the experimental samples. This design with tissue matched reference samples allows a gene-by-gene correction to be performed using fewer arrays than currently available methods. We examine the effects of non-biological variation within a single experiment and between experiments.
Batch correction has a significant impact on which genes are identified as differentially regulated. Using this method, gene expression in the blood of patients with Duchenne Muscular Dystrophy is shown to differ for hundreds of genes when compared to controls. The numbers of specific genes differ depending upon whether between experiment and/or between batch corrections are performed.
BMC Genomics 11/2008; 9:494. · 4.07 Impact Factor
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ABSTRACT: Abstract
Background
Non-biological experimental error routinely occurs in microarray data collected in different batches. It is often impossible to compare groups of samples from independent experiments because batch effects confound true gene expression differences. Existing methods can correct for batch effects only when samples from all biological groups are represented in every batch.
Results
In this report we describe a generalized empirical Bayes approach to correct for cross-experimental batch effects, allowing direct comparisons of gene expression between biological groups from independent experiments. The proposed experimental design uses identical reference samples in each batch in every experiment. These reference samples are from the same tissue as the experimental samples. This design with tissue matched reference samples allows a gene-by-gene correction to be performed using fewer arrays than currently available methods. We examine the effects of non-biological variation within a single experiment and between experiments.
Conclusion
Batch correction has a significant impact on which genes are identified as differentially regulated. Using this method, gene expression in the blood of patients with Duchenne Muscular Dystrophy is shown to differ for hundreds of genes when compared to controls. The numbers of specific genes differ depending upon whether between experiment and/or between batch corrections are performed.
BMC Genomics. 01/2008;
