Metaanalysis of flawed expression profiling data leading to erroneous Parkinson's biomarker identification.
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ABSTRACT:
SUBMITTER: Toker L
PROVIDER: S-EPMC4507209 | biostudies-literature | 2015 Jul
REPOSITORIES: biostudies-literature
Publications
Metaanalysis of flawed expression profiling data leading to erroneous Parkinson's biomarker identification.
Proceedings of the National Academy of Sciences of the United States of America 20150623 28
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Project description:BackgroundParkinson's disease (PD) is a neurodegenerative disorder. The diagnosis of Parkinsonism is challenging because currently none of the clinical tests have been proven to help in diagnosis. PD may produce characteristic perturbations in the metabolome and such variations can be used as the marker for detection of disease. To test this hypothesis, we used proton NMR and multivariate analysis followed by neural network pattern detection.Methods & results1H nuclear magnetic resonance spectroscopy analysis was carried out on plasma samples of 37 healthy controls and 43 drug-naive patients with PD. Focus on 22 targeted metabolites, 17 were decreased and 5 were elevated in PD patients (p < 0.05). Partial least squares discriminant analysis (PLS-DA) showed that pyruvate is the key metabolite, which contributes to the separation of PD from control samples. Furthermore, gene expression analysis shows significant (p < 0.05) change in expression of PDHB and NPFF genes leading to increased pyruvate concentration in blood plasma. Moreover, the implementation of 1H- NMR spectral pattern in neural network algorithm shows 97.14% accuracy in the detection of disease progression.ConclusionThe results increase the prospect of a robust molecular definition in detection of PD through the early symptomatic phase of the disease. This is an ultimate opening for therapeutic intervention. If validated in a genuinely prospective fashion in larger samples, the biomarker trajectories described here will go a long way to facilitate the development of useful therapies. Moreover, implementation of neural network will be a breakthrough in clinical screening and rapid detection of PD.
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Project description:Glycans are primarily generated by "glycogenes," which consist of more than 200 genes for glycosynthesis, including sugar-nucleotide synthases, sugar-nucleotide transporters, and glycosyltransferases. Measuring the expression level of glycogenes is one of the approaches to analyze the glycomes of particular biological and clinical samples. To develop an effective strategy for identifying the glycosylated biomarkers, we performed transcriptome analyses using quantitative real-time polymerase chain reaction (qRT-PCR) arrays and RNA sequencing (RNA-Seq). First, we measured and analyzed the transcriptome from the primary culture of human liver cells and hepatocarcinoma cells using RNA-Seq. This analysis revealed similar but distinctive expression profiles of glycogenes among hepatic cells as indicated by the qRT-PCR arrays, which determined a copy number of 186 glycogenes. Both data sets indicated that altered expression of glycosyltransferases affect the glycosylation of particular glycoproteins, which is consistent with the mass analysis data. Moreover, RNA-Seq analysis can uncover mutations in glycogenes and search differently expressed genes out of more than 50,000 distinct human gene transcripts including candidate biomarkers that were previously reported for hepatocarcinoma cells. Identification of candidate glyco-biomarkers from the expression profile of the glycogenes and proteins from liver cancer tissues available from public database emphasized the possibility that even though the expression level of biomarkers might not be altered, the expression of the glycogenes modifying biomarkers, generating glyco-biomarkers, might be different. Pathway analysis revealed that ~20% of the glycogenes exhibited different expression levels in normal and cancer cells. Thus, transcriptome analyses using both qRT-PCR array and RNA-Seq in combination with glycome and glycoproteome analyses can be advantageous to identify "glyco-biomarkers" by reinforcing information at the expression levels of both glycogenes and proteins.
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Project description:Parkinson's disease (PD) is a growing burden worldwide, and there is no reliable biomarker used in clinical routines to date. Cerebrospinal fluid (CSF) is routinely collected in patients with neurological symptoms and should closely reflect alterations in PD patients' brains. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomics workflow for CSF proteome profiling. From two independent cohorts with over 200 individuals, our workflow reproducibly quantifies over 1,700 proteins from minimal CSF amounts. Machine learning determines OMD, CD44, VGF, PRL, and MAN2B1 to be altered in PD patients or to significantly correlate with clinical scores. We also uncover signatures of enhanced neuroinflammation in LRRK2 G2019S carriers, as indicated by increased levels of CTSS, PLD4, and HLA proteins. A comparison with our previously acquired urinary proteomes reveals a large overlap in PD-associated changes, including lysosomal proteins, opening up new avenues to improve our understanding of PD pathogenesis.
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Project description:BACKGROUND: In the postgenome era, a prediction of response to treatment could lead to better dose selection for patients in radiotherapy. To identify a radiosensitive gene signature and elucidate related signaling pathways, four different microarray experiments were reanalyzed before radiotherapy. RESULTS: Radiosensitivity profiling data using clonogenic assay and gene expression profiling data from four published microarray platforms applied to NCI-60 cancer cell panel were used. The survival fraction at 2?Gy (SF2, range from 0 to 1) was calculated as a measure of radiosensitivity and a linear regression model was applied to identify genes or a gene set with a correlation between expression and radiosensitivity (SF2). Radiosensitivity signature genes were identified using significant analysis of microarrays (SAM) and gene set analysis was performed using a global test using linear regression model. Using the radiation-related signaling pathway and identified genes, a genetic network was generated. According to SAM, 31 genes were identified as common to all the microarray platforms and therefore a common radiosensitivity signature. In gene set analysis, functions in the cell cycle, DNA replication, and cell junction, including adherence and gap junctions were related to radiosensitivity. The integrin, VEGF, MAPK, p53, JAK-STAT and Wnt signaling pathways were overrepresented in radiosensitivity. Significant genes including ACTN1, CCND1, HCLS1, ITGB5, PFN2, PTPRC, RAB13, and WAS, which are adhesion-related molecules that were identified by both SAM and gene set analysis, and showed interaction in the genetic network with the integrin signaling pathway. CONCLUSIONS: Integration of four different microarray experiments and gene selection using gene set analysis discovered possible target genes and pathways relevant to radiosensitivity. Our results suggested that the identified genes are candidates for radiosensitivity biomarkers and that integrin signaling via adhesion molecules could be a target for radiosensitization.
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Project description:BackgroundOne challenge of systems biology is the integration of new data into the preexisting, and then re-interpretation of the integrated data. Here we use readily available metaanalysis computational methods to integrate new data on the transcriptomic effects of EGF in primary human epidermal keratinocytes with preexisting transcriptomics data in keratinocytes and in EGF-treated non-epidermal cell types.ResultsWe find that EGF promotes keratinocyte proliferation, attachment and motility and, surprisingly, induces DUSPs that attenuate the EGF signal. Our metaanalysis identified overlapping effects of EGF with those of IL-1 and IFNγ, activators of keratinocyte in inflammation and wound healing. We also identified the genes and pathways suppressed by EGF but induced by agents promoting epidermal differentiation. Metaanalysis comparison with the EGF effects in other cell types identified extensive similarities between responses in keratinocytes and in other epithelial cell types, but specific differences with the EGF effects in endothelial cells, and in transformed, oncogenic epithelial cell lines.ConclusionsThis work defines the specific transcriptional effects of EGF on human epidermal keratinocytes. Our approach can serve as a suitable paradigm for integration of new omics data into preexisting databases and re-analysis of the integrated data sets.
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Project description:The current study aimed to isolate key transcription factors (TFs) in caerulein-induced pancreatitis, and to identify the difference between wild type and Mist1 knockout (KO) mice, in order to elucidate the contribution of Mist1 to pancreatitis. The gene profile of GSE3644 was downloaded from the Gene Expression Omnibus database then analyzed using the t-test. The isolated differentially expressed genes (DEGs) were mapped into a transcriptional regulatory network derived from the Integrated Transcription Factor Platform database and in the network, the interaction pairs involving at least one DEG were screened. Fisher's exact test was used to analyze the functional enrichment of the target genes. A total of 1,555 and 3,057 DEGs were identified in the wild type and Mist1KO mice treated with caerulein, respectively. DEGs screened in Mist1KO mice were predominantly enriched in apoptosis, mitogen-activated protein kinase signaling and other cancer-associated pathways. A total of 188 and 51 TFs associated with pathopoiesis were isolated in Mist1KO and wild type mice, respectively. Out of the top 10 TFs (ranked by P-value), 7 TFs, including S-phase kinase-associated protein 2 (Skp2); minichromosome maintenance complex component 3 (Mcm3); cell division cycle 6 (Cdc6); cyclin B1 (Ccnb1); mutS homolog 6 (Msh6); cyclin A2 (Ccna2); and cyclin B2 (Ccnb2), were expressed in the two types of mouse. These TFs were predominantly involved in phosphorylation, DNA replication, cell division and DNA mismatch repair. In addition, specific TFs, including minichromosome maintenance complex component 7 (Mcm7); lymphoid-specific helicase (Hells); and minichromosome maintenance complex component 6 (Mcm6), that function in the unwinding of DNA were identified to participate in Mist1KO pancreatitis. The DEGs, including Cdc6, Mcm6, Msh6 and Wdr1 are closely associated with the regulation of caerulein-induced pancreatitis. Furthermore, other identified TFs were also involved in this type of regulation.
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Project description:ObjectiveElectronic data collection (EDC) has become a suitable alternative to paper based data collection (PBDC) in biomedical research even in resource poor settings. During a survey in Nepal, data were collected using both systems and data entry errors compared between both methods. Collected data were checked for completeness, values outside of realistic ranges, internal logic and date variables for reasonable time frames. Variables were grouped into 5 categories and the number of discordant entries were compared between both systems, overall and per variable category.ResultsData from 52 variables collected from 358 participants were available. Discrepancies between both data sets were found in 12.6% of all entries (2352/18,616). Differences between data points were identified in 18.0% (643/3580) of continuous variables, 15.8% of time variables (113/716), 13.0% of date variables (140/1074), 12.0% of text variables (86/716), and 10.9% of categorical variables (1370/12,530). Overall 64% (1499/2352) of all discrepancies were due to data omissions, 76.6% (1148/1499) of missing entries were among categorical data. Omissions in PBDC (n = 1002) were twice as frequent as in EDC (n = 497, p < 0.001). Data omissions, specifically among categorical variables were identified as the greatest source of error. If designed accordingly, EDC can address this short fall effectively.
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Project description:Environmental and genetic factors are likely to be involved in the pathogenesis of Parkinson's disease (PD), the second most prevalent neurodegenerative disease among the elderly. Network-based metaanalysis of four independent microarray studies identified the hepatocyte nuclear factor 4 alpha (HNF4A), a transcription factor associated with gluconeogenesis and diabetes, as a central regulatory hub gene up-regulated in blood of PD patients. In parallel, the polypyrimidine tract binding protein 1 (PTBP1), involved in the stabilization and mRNA translation of insulin, was identified as the most down-regulated gene. Quantitative PCR assays revealed that HNF4A and PTBP1 mRNAs were up- and down-regulated, respectively, in blood of 51 PD patients and 45 controls nested in the Diagnostic and Prognostic Biomarkers for Parkinson's Disease. These results were confirmed in blood of 50 PD patients compared with 46 healthy controls nested in the Harvard Biomarker Study. Relative abundance of HNF4A mRNA correlated with the Hoehn and Yahr stage at baseline, suggesting its clinical utility to monitor disease severity. Using both markers, PD patients were classified with 90% sensitivity and 80% specificity. Longitudinal performance analysis demonstrated that relative abundance of HNF4A and PTBP1 mRNAs significantly decreased and increased, respectively, in PD patients during the 3-y follow-up period. The inverse regulation of HNF4A and PTBP1 provides a molecular rationale for the altered insulin signaling observed in PD patients. The longitudinally dynamic biomarkers identified in this study may be useful for monitoring disease-modifying therapies for PD.
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Project description:Molecular analyses of biliary brushings using microarray and qPCR have the potential to provide valuable information on the biology of biliary diseases. Microarray analysis of biliary strictures has rarely been applied to endoscopic biliary brushings.Biliary brushings were obtained from patients with benign and malignant biliary disease at the time of ERCP. Microarray analysis of mRNA isolated using brushings from 10 patients was validated for a selection of genes by qPCR using the same source mRNA and a second fresh set of nine biliary brushings as well as surgical resection tissue. Cultured cholangiocytes were used to assess the impact of bile or X-ray contrast solution on RNA quality.RNA was of variable quantity (100-1500 ng) and poor quality (Agilent RNA Integrity Number (RIN)<5, estimated to be fragments 100 to 600 base pairs long). Reliable qPCR results required primer pairs designed to produce amplicons <130 bp. Differential gene expression by microarray analysis identified 1140 up-regulated genes and 1001 down-regulated genes between benign and malignant biliary strictures. The trends in a selection of 45 up-regulated genes, including various HOX genes, collagens, PVT1, MUC4, MUC5AC, and LEF1, were validated by qPCR using RNA from biliary strictures with a moderate to strong correlation coefficient between microarray and qPCR (r=0.41 to r=0.57). Immunohistochemistry of surgical resection tissues (n=23) showed elevated CD9, SERPINA3, and PNMA2 protein expression in cancer samples.RNA isolated from biliary brushings is suitable for molecular analysis of biliary diseases using qPCR and microarray.
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