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Biomedical subjects

Rafael A Irizarry

Publications and source records attributed to Rafael A Irizarry.

At least 19 recordsLinked to original sources
PubMed2005

Global synthetic-lethality analysis and yeast functional profiling.

The Saccharomyces genome-deletion project created >5900 'molecularly barcoded' yeast knockout mutants (YKO mutants). The YKO mutant collections have facilitated large-scale analyses of a multitude of mutant phenotypes. For example, both synthetic genetic array (SGA) and synthetic-lethality analysis by microarray (SLAM) methods have been used for synthetic-lethality screens. Global analysis of synthetic lethality promises to identify cellular pathways that 'buffer' each other biologically. The combination of global synthetic-lethality analysis, together with global protein-protein interaction analyses, mRNA expression profiling and functional profiling will, in principle, enable construction of a cellular 'wiring diagram' that will help frame a deeper understanding of human biology and disease.

Chromosome Mapping↗
PubMed2005

Improved statistical analysis of budding yeast TAG microarrays revealed by defined spike-in pools.

Saccharomyces cerevisiae knockout collection TAG microarrays are an emergent platform for rapid, genome-wide functional characterization of yeast genes. TAG arrays report abundance of unique oligonucleotide 'TAG' sequences incorporated into each deletion mutation of the yeast knockout collection, allowing measurement of relative strain representation across experimental conditions for all knockout mutants simultaneously. One application of TAG arrays is to perform genome-wide synthetic lethality screens, known as synthetic lethality analyzed by microarray (SLAM). We designed a fully defined spike-in pool to resemble typical SLAM experiments and performed TAG microarray hybridizations. We describe a method for analyzing two-color array data to efficiently measure the differential knockout strain representation across two experimental conditions, and use the spike-in pool to show that the sensitivity and specificity of this method exceed typical current approaches.

Data Interpretation, Statistical↗
PubMed2005

Gene expression in giant cell myocarditis: Altered expression of immune response genes.

BACKGROUND: Giant cell myocarditis is a rapidly progressive and often fatal condition without a clear etiology or treatment. A better understanding of giant cell myocarditis pathogenesis is critical to developing treatments to prevent progression and reverse damage. We compared the gene expression of giant cell myocarditis with that of nonfailing hearts. METHODS: Left ventricular samples from two giant cell myocarditis patients harvested during ventricular assist device placement and six unused donor hearts were examined using Affymetrix U133A microarrays. Differential gene expression was defined with a Bonferroni-adjusted p value < or = 0.05 from a Student's t-test and an absolute fold change > or = 2.0. Select gene expression was confirmed with quantitative PCR. RESULTS: Of 115 differentially expressed genes, most were upregulated in giant cell myocarditis and involved in immune response, transcriptional regulation, and metabolism. T-cell activation genes included chemokine receptor 4; chemokine ligands 5, 9, 13, and 18; interleukin-10 receptor alpha; and beta-2 integrin. CONCLUSIONS: Gene expression analysis of giant cell myocarditis offers novel insights into its pathogenesis, namely the role of T-cell activators of the Th1 subset and immune response genes previously implicated in heart failure. This forms the basis for future work aimed at defining novel therapeutic targets for giant cell myocarditis.

Adult↗
PubMed2005

Improved microarray methods for profiling the Yeast Knockout strain collection.

A remarkable feature of the Yeast Knockout strain collection is the presence of two unique 20mer TAG sequences in almost every strain. In principle, the relative abundances of strains in a complex mixture can be profiled swiftly and quantitatively by amplifying these sequences and hybridizing them to microarrays, but TAG microarrays have not been widely used. Here, we introduce a TAG microarray design with sophisticated controls and describe a robust method for hybridizing high concentrations of dye-labeled TAGs in single-stranded form. We also highlight the importance of avoiding PCR contamination and provide procedures for detection and eradication. Validation experiments using these methods yielded false positive (FP) and false negative (FN) rates for individual TAG detection of 3-6% and 15-18%, respectively. Analysis demonstrated that cross-hybridization was the chief source of FPs, while TAG amplification defects were the main cause of FNs. The materials, protocols, data and associated software described here comprise a suite of experimental resources that should facilitate the use of TAG microarrays for a wide variety of genetic screens.

Coloring Agents↗
PubMed2005

In vitro identification and in silico utilization of interspecies sequence similarities using GeneChip technology.

BACKGROUND: Genomic approaches in large animal models (canine, ovine etc) are challenging due to insufficient genomic information for these species and the lack of availability of corresponding microarray platforms. To address this problem, we speculated that conserved interspecies genetic sequences can be experimentally detected by cross-species hybridization. The Affymetrix platform probe redundancy offers flexibility in selecting individual probes with high sequence similarities between related species for gene expression analysis. RESULTS: Gene expression profiles of 40 canine samples were generated using the human HG-U133A GeneChip (U133A). Due to interspecies genetic differences, only 14 +/- 2% of canine transcripts were detected by U133A probe sets whereas profiling of 40 human samples detected 49 +/- 6% of human transcripts. However, when these probe sets were deconstructed into individual probes and examined performance of each probe, we found that 47% of human probes were able to find their targets in canine tissues and generate a detectable hybridization signal. Therefore, we restricted gene expression analysis to these probes and observed the 60% increase in the number of identified canine transcripts. These results were validated by comparison of transcripts identified by our restricted analysis of cross-species hybridization with transcripts identified by hybridization of total lung canine mRNA to new Affymetrix Canine GeneChip. CONCLUSION: The experimental identification and restriction of gene expression analysis to probes with detectable hybridization signal drastically increases transcript detection of canine-human hybridization suggesting the possibility of broad utilization of cross-hybridizations of related species using GeneChip technology.

Animals↗
PubMed2005

Multiple-laboratory comparison of microarray platforms.

Microarray technology is a powerful tool for measuring RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of cross-platform meta-analysis studies rapidly increases, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we noticed that none of the previously published papers consider differences between labs. For this study, a consortium of ten laboratories from the Washington, DC-Baltimore, USA, area was formed to compare data obtained from three widely used platforms using identical RNA samples. We used appropriate statistical analysis to demonstrate that there are relatively large differences in data obtained in labs using the same platform, but that the results from the best-performing labs agree rather well.

Baltimore↗
PubMed2005

Gene expression analysis of ischemic and nonischemic cardiomyopathy: shared and distinct genes in the development of heart failure.

Cardiomyopathy can be initiated by many factors, but the pathways from unique inciting mechanisms to the common end point of ventricular dilation and reduced cardiac output are unclear. We previously described a microarray-based prediction algorithm differentiating nonischemic (NICM) from ischemic cardiomyopathy (ICM) using nearest shrunken centroids. Accordingly, we tested the hypothesis that NICM and ICM would have both shared and distinct differentially expressed genes relative to normal hearts and compared gene expression of 21 NICM and 10 ICM samples with that of 6 nonfailing (NF) hearts using Affymetrix U133A GeneChips and significance analysis of microarrays. Compared with NF, 257 genes were differentially expressed in NICM and 72 genes in ICM. Only 41 genes were shared between the two comparisons, mainly involved in cell growth and signal transduction. Those uniquely expressed in NICM were frequently involved in metabolism, and those in ICM more often had catalytic activity. Novel genes included angiotensin-converting enzyme-2 (ACE2), which was upregulated in NICM but not ICM, suggesting that ACE2 may offer differential therapeutic efficacy in NICM and ICM. In addition, a tumor necrosis factor receptor was downregulated in both NICM and ICM, demonstrating the different signaling pathways involved in heart failure pathophysiology. These results offer novel insight into unique disease-specific gene expression that exists between end-stage cardiomyopathy of different etiologies. This analysis demonstrates that transcriptome analysis offers insight into pathogenesis-based therapies in heart failure management and complements studies using expression-based profiling to diagnose heart failure of different etiologies.

Angiotensin-Converting Enzyme 2↗
PubMed2005

Oligonucleotide-microarray analysis of peripheral-blood lymphocytes in severe asthma.

CD4 + lymphocytes play a key role in asthma pathogenesis, but much remains unknown about the genetic mechanisms that affect disease severity. In this study we sought to investigate global patterns of gene expression in CD4 + lymphocytes isolated from subjects with severe asthma through the use of microarray technology. CD4 + lymphocytes were separated from peripheral blood, total RNA was purified, and biotinylated complementary RNA was prepared and hybridized to Affymetrix HU133 chips (Affymetrix, Santa Clara, Calif). Using the robust multi-chip average procedure, we compared the messenger RNA expression profiles of more than 33,000 genes of CD4 + lymphocytes in subjects with severe ( n = 5) and mild ( n = 5) asthma. Forty genes had 2-fold mean expression differences or greater. Thirty-seven genes were up-regulated, including transforming growth factor-beta and those involved in T-cell activation, proliferation, and cytoskeletal changes. Three genes were down-regulated, including the T-cell-receptor delta locus. This study demonstrates a method by which CD4 + lymphocytes can be extracted from blood for the purpose of microarray analysis. Furthermore, we show that T-lymphocytes from the peripheral blood of subjects with severe and mild asthma differ in their gene-expression profiles, supporting the view that asthma is a systemic disease. These differentially expressed genes identify potential molecular targets for preventive and therapeutic options for severe asthma.

Adult↗
PubMed2005

The External RNA Controls Consortium: a progress report.

Standard controls and best practice guidelines advance acceptance of data from research, preclinical and clinical laboratories by providing a means for evaluating data quality. The External RNA Controls Consortium (ERCC) is developing commonly agreed-upon and tested controls for use in expression assays, a true industry-wide standard control.

Animals↗
PubMed2004

Identification of a gene expression profile that differentiates between ischemic and nonischemic cardiomyopathy.

BACKGROUND: Gene expression profiling refines diagnostic and prognostic assessment in oncology but has not yet been applied to myocardial diseases. We hypothesized that gene expression differentiates ischemic and nonischemic cardiomyopathy, demonstrating that gene expression profiling by clinical parameters is feasible in cardiology. METHODS AND RESULTS: Affymetrix U133A microarrays of 48 myocardial samples from Johns Hopkins Hospital (JHH) and the University of Minnesota (UM) obtained (1) at transplantation or left ventricular assist device (LVAD) placement (end-stage; n=25), (2) after LVAD support (post-LVAD; n=16), and (3) from newly diagnosed patients (biopsy; n=7) were analyzed with prediction analysis of microarrays. A training set was used to develop the profile and test sets to validate the accuracy of the profile. An etiology prediction profile developed in end-stage JHH samples was tested in independent samples from both JHH and UM with 100% sensitivity and 100% specificity in end-stage samples and 33% sensitivity and 100% specificity in both post-LVAD and biopsy samples. The overall sensitivity was 89% (95% CI 75% to 100%), and specificity was 89% (95% CI 60% to 100%) over 210 random partitions of end-stage samples into training and test sets. Age, gender, and hemodynamic differences did not affect the profile's accuracy in stratified analyses. Select gene expression was confirmed with quantitative polymerase chain reaction. CONCLUSIONS: Gene expression profiling accurately predicts cardiomyopathy etiology, is generalizable to samples from separate institutions, is specific to disease stage, and is unaffected by differences in clinical characteristics. This strongly supports ongoing efforts to incorporate expression profiling-based biomarkers in determining prognosis and response to therapy in heart failure.

Adult↗
PubMed2004

Orthologous gene-expression profiling in multi-species models: search for candidate genes.

Microarray-driven gene-expression profiles are generally produced and analyzed for a single specific experimental model. We have assessed an analytical approach that simultaneously evaluates multi-species experimental models within a particular biological condition using orthologous genes as linkers for the various Affymetrix microarray platforms on multi-species models of ventilator-associated lung injury. The results suggest that this approach may be a useful tool in the evaluation of biological processes of interest and selection of process-related candidate genes.

Animals↗
PubMed2004

affy--analysis of Affymetrix GeneChip data at the probe level.

MOTIVATION: The processing of the Affymetrix GeneChip data has been a recent focus for data analysts. Alternatives to the original procedure have been proposed and some of these new methods are widely used. RESULTS: The affy package is an R package of functions and classes for the analysis of oligonucleotide arrays manufactured by Affymetrix. The package is currently in its second release, affy provides the user with extreme flexibility when carrying out an analysis and make it possible to access and manipulate probe intensity data. In this paper, we present the main classes and functions in the package and demonstrate how they can be used to process probe-level data. We also demonstrate the importance of probe-level analysis when using the Affymetrix GeneChip platform.

Algorithms↗
PubMed2004

A benchmark for Affymetrix GeneChip expression measures.

MOTIVATION: The defining feature of oligonucleotide expression arrays is the use of several probes to assay each targeted transcript. This is a bonanza for the statistical geneticist, who can create probeset summaries with specific characteristics. There are now several methods available for summarizing probe level data from the popular Affymetrix GeneChips, but it is difficult to identify the best method for a given inquiry. RESULTS: We have developed a graphical tool to evaluate summaries of Affymetrix probe level data. Plots and summary statistics offer a picture of how an expression measure performs in several important areas. This picture facilitates the comparison of competing expression measures and the selection of methods suitable for a specific investigation. The key is a benchmark data set consisting of a dilution study and a spike-in study. Because the truth is known for these data, we can identify statistical features of the data for which the expected outcome is known in advance. Those features highlighted in our suite of graphs are justified by questions of biological interest and motivated by the presence of appropriate data.

Algorithms↗
PubMed2004

Travelling waves in the occurrence of dengue haemorrhagic fever in Thailand.

Dengue fever is a mosquito-borne virus that infects 50-100 million people each year. Of these infections, 200,000-500,000 occur as the severe, life-threatening form of the disease, dengue haemorrhagic fever (DHF). Large, unanticipated epidemics of DHF often overwhelm health systems. An understanding of the spatial-temporal pattern of DHF incidence would aid the allocation of resources to combat these epidemics. Here we examine the spatial-temporal dynamics of DHF incidence in a data set describing 850,000 infections occurring in 72 provinces of Thailand during the period 1983 to 1997. We use the method of empirical mode decomposition to show the existence of a spatial-temporal travelling wave in the incidence of DHF. We observe this wave in a three-year periodic component of variance, which is thought to reflect host-pathogen population dynamics. The wave emanates from Bangkok, the largest city in Thailand, moving radially at a speed of 148 km per month. This finding provides an important starting point for detecting and characterizing the key processes that contribute to the spatial-temporal dynamics of DHF in Thailand.

Geography↗
PubMed2004

Leydig cell gene expression: effects of age and caloric restriction.

In mammals, the concentration of testosterone in blood serum typically becomes reduced with aging. We have shown that, in rats, this results from reduced testosterone production by individual Leydig cells. To gain an understanding of the mechanisms by which Leydig cell steroidogenic function changes with aging, we compared the gene expression profiles in Leydig cells isolated from young and old Brown Norway rats, focusing on possible changes in genes involved in, or associated with, steroidogenesis. We also explored the effects of caloric restriction, an intervention shown to delay or inhibit age-associated pathologic and biologic changes in a number of systems and organisms, on the expression of these genes. Of the total of 1176 genes arrayed on each of the five membranes per group that we used, about 500 (45%) were detectable in Leydig cells isolated from young and old rat testes, with the same genes detectable in cells from both ages. An ANOVA model was applied to statistically analyze the 500 detectable genes in the four treatment groups. The primary criterion by which interesting genes were selected was a P value of </=0.05. With aging, a large number of genes were seen with fold changes of >1.5. However, when P</=0.05 was used as the selection criterion, only 45 genes were seen to change significantly with age. Most, but not all, of these genes also had fold changes of >1.5. Among the 500 genes, 17 were found to decrease in expression with aging, the most prominent among which were genes involved in steroidogenesis and stress response/free radical scavenging. Long-term caloric restriction had little effect on the 45 genes altered by age. In contrast to the effects of caloric restriction as seen in many other cell types and systems, the vast majority (44/45) of the Leydig cell genes that changed with age were not 'rescued' by this intervention.

Aging↗
PubMed2004

The psychophysiology of the maternal-fetal relationship.

The enigmatic quality of the maternal-fetal relationship has been extolled throughout history with little empirical support. We apply time series analysis to data for 137 maternal-fetal pairs collected at 20, 24, 28, 32, 36, and 38 weeks gestation. Maternal heart rate and skin conductance data were digitized in tandem with fetal heart rate and motor activity. No temporal relations between fetal heart rate and either maternal variable were found, although averaged maternal and fetal heart rates were correlated from 32 weeks. Consistent temporal associations between fetal movement and maternal heart rate and skin conductance were detected. Fetal movement stimulated rises in each parameter, peaking at 2 and 3 s, respectively. Associations did not change over gestation, were unaffected by a maternal stressor, and showed within-pair stability. The bidirectional nature of the maternal-fetal relationship is considered.

Adult↗
PubMed2003

Deficiency of different nitric oxide synthase isoforms activates divergent transcriptional programs in cardiac hypertrophy.

Decreased nitric oxide synthase (NOS) activity induces left ventricular hypertrophy (LVH), but the transcriptional pathways mediating this effect are unknown. We hypothesized that specific NOS isoform deletion (NOS3 or NOS1) would activate different transcriptional programs in LVH. We analyzed cardiac expression profiles (Affymetrix MG-U74A) from NOS-/- mice using robust multi-array average (RMA). Of 12,422 genes analyzed, 47 genes were differentially expressed in NOS3-/- and 67 in NOS1(-/-) hearts compared with wild type (WT). Only 16 showed similar changes in both NOS-/- strains, most notably decreased heat-shock proteins (HSP10, 40, 70, 86, 105). Hypertrophied NOS1-/- hearts had unique features, including decreased myocyte-enriched calcineurin interacting protein and paradoxical downregulation of fetal isoforms (alpha-skeletal actin and brain natriuretic peptide). Cluster analyses demonstrated that NOS1 deletion caused more pronounced changes in the myocardial transcriptome than did NOS3 deletion, despite similar cardiac phenotypes. These findings suggest that the transcriptional basis for LVH varies depending on the inciting biochemical stimulus. In addition, NOS isoforms appear to play distinct roles in modulating cardiac structure.

Animals↗