Van Eyk, Dunn - Proteomic and Genomic Analysis of Cardiovascular Disease - 2003 (522919), страница 9
Текст из файла (страница 9)
MGED has submitted their proposal for MAGE-ML to theObject Management Group (OMG), an organization that develops industry guidelines and defines standards for software application development. Once these standards have been established, data exchange between laboratories will depend mainlyon the willingness of individual researchers to share their expression data with theresearch community, or on scientific journals to enforce the release of the primarydata upon publication of a microarray study.1.3Potential Use of This Technology in Understanding Complex Heart DiseaseLarge-scale expression analysis is a potentially powerful tool to characterize complex disease traits.
Therefore, many scientists have used microarrays [24, 25, 51,55–61] or other expression profiling technologies, such as subtraction [23, 62] orGeneCalling [63] to elucidate the transcriptional profiles in experimental modelsand human patient samples related to cardiac hypertrophy and heart failure(summarized in Tab. 1.2).Hypertrophy is a universal adaptive response to increased cardiac workload,stress, and injury that can be induced by many different stimuli. Microarray expression profiling studies have been performed on models for pressure-overloadinduced hypertrophy [62, 63]; hypertrophy induced by Isoproterenol and AngiotensinII [58]; hypertrophy induced by transgenic overexpression of Calsequestrin, Calcineurin, Gaq, and WeRack [51], as well as on models of myocardial infarction [25,55–57].
Ideally, comparison of these (in some aspects) phenotypically similar, butpathophysiological dissimilar models would enable us to differentiate among themultiple processes that cause hypertrophy (and heart failure), and to identify patterns of gene expression that are either common for these diseases or specific fora certain subset of conditions.Unfortunately, direct comparison of results between these studies is nearly impossible due to substantial differences in the technology platforms being used, thenumber of transcripts being interrogated or sequenced, differences in experimental conditions and data analysis, and tissue-types that are being compared(Tab.
1.2). Given these differences, there is generally little overlap in the numberand identity of genes that are differentially expressed between these studies. Still,some consensus can be found, like an induction of expression of the atrial andbrain natriuretic peptide genes ANP and BNP, and extracellular matrix genes incardiac hypertrophy, or an induction of genes involved in stress response, inflammation and wound healing in different models of myocardial infarction. Most ofthese changes confirm findings that have already been reported previously.However, individual studies identify new sets of differentially expressed genesthat have not yet been implicated in the disease under study, such as a decreaseMouseRatRatRatExperimental MIExperimental MIACE inhibition afterexperimental MICHF afterexperimental MIMouseMousePressure-overloadhypertrophyHypertrophy, AIIand ISO-inducedPressure-overloadRatinduced hypertrophyPigTransient ischemiaMethodLVTotal heartWhole heartLVLVLV free wallversus IVSTotal ventriclecDNA arraySubtractionGeneCallingHeart cDNAarrayOligonucleotidearray(Affymetrix)Heart cDNAarraycDNA array(Clontech)LV ischemicSubtractionand control areaSpecies TissueModel8,000/374,258/230588/78481114,000/35910018,000/74fragments(23 genes)Induction of secreted factors, structural genes,genes related to energy metabolism, and differentsignaling pathwaysUpregulation of genes involved in transcription,translation; proteins that form or regulate thecytoskeleton; and genes involved in signalingElevated expression of ECM genes and secretedfactorsUpregulation of natriuretic petides ANF andBNP, matrix genes, and genes that are involvedin wound healing, infiltrating mononuclearphagocytes, and vascular reactivityUpregulation of natriuretic genes, ECM genes,genes involved in inflammation/wound healing,and muscle proteinsChanges in expression of genes that areimplicated in cytoskeletal architecture, ECM,contractility, and metabolismUpregulation of genes associated with heartmuscle development and stress responseUpregulation of genes involved in survivalmechanismTranscriptsFindingson the array/changed *4–7 1,075/686411n14 (AII), 17 (ISO)1161511TimepointsTab.
1.2 Publications on cardiovascular diseases using large scale expression profiling technologies[58][62][63][56][25][57][55][23]Ref.1.3 Potential Use of This Technology in Understanding Complex Heart Disease21MouseRatHuman Not specifiedHuman LV free wallMouseHypertrophy in 4transgenic modelsExposure to IGF-1End-stage hypertrophic cardiomyopathyEnd-stage ICMand DCMMyocarditisRat heart cDNAarray (Incyte)3Oligonucleotide1array (Affymetrix)141.2 cDNA array(Clontech)Heart cDNAarray1TimepointscDNA array(Incyte)Method12161n4,200/1696,800/1910,368/381,193/688,800/276[24][60][59][51]Ref.Upregulation of genes related to viral replication, [61]host defense, metabolic changes, and ECM proteinsAltered expression of cytoskeletal and myofibrillar genes, genes involved in protein degradation, stress response, and metabolismIdentification of several genes that showdifferential expression in heart failureUpregulation of genes involved in intracellularsignaling, cell cycle, transcription/translation,cellular respiration and mitochondrial function,cell survival, ion channels and calcium signaling,and humoral factorsNo genes are found to be regulated in commonamong the 4 models.
A set of apoptotic genes isuniquely upregulated in the Gaq modelTranscriptsFindingson the array/changed ** The number of transcripts listed in the table might include redundant transcripts; the actual number of interrogated genes might be lower. AII angiotensin II;DCM dilated cardiomyopathy; ECM extracellular matrix, ICM ischemic cardiomyopathy; ISO isoproterenol, IVS intraventricular septum; LV left ventricle; MI myocardial infarction; n number of replicates.Whole heartNeonatalventricularcardiomyocytesLVSpecies TissueModelTab. 1.2 (continued)221 Microarray Expression Profiling in Cardiovascular Disease1-4 Acknowledgementsin SLIM1 (striated muscle LIM protein-1) expression and an increase in gelsolinexpression in failing human hearts [24].
The degree of confidence in the dataquality and analysis depends on whether replicate experiments were performed,dye-swaps were used to adjust for differences in labeling efficiencies (for cDNAmicroarrays), how cut-off values were determined in order to identify differentiallyexpressed genes, and whether or not differential gene expression was confirmedby alternative methods, such as Northern blotting or RT-PCR. Also, were the tissues and time points chosen appropriate for the questions asked? For example, incases where the whole left ventricle was used for analysis, it is questionablewhether the sensitivity was sufficient to survey genes whose differential expression is confined to a specific region of the heart, such as the infarcted area. Additional confidence and potentially new insight would be gained if the completedata set, the raw data, and an explicit description of the experimental conditionswould be available for other laboratories to reproduce the results.
Although datasupplements of extended gene lists and additional method descriptions were available in some cases [57], none of the microarray studies cited above provided access to their raw data. Finally, every new hypothesis has to be further tested inbiological systems, such as through transgenic overexpression, dominant-negative,antisense, or gene targeting strategies, in order to establish a causal relationshipof the change in gene expression with the disease – one gene at a time.Although it becomes clear that microarrays hold much promise for the analysisof cardiovascular diseases, many of these studies illustrate the experimental andtechnological hurdles imposed by current technologies.
This includes the fact thatgenome-wide chips are still unavailable for most species. Currently available arrays cover only a fraction of genes in the genome, setting a limit to the numberof differentially expressed genes that can be detected. Some laboratories tried toincrease the number of genes that are potentially involved in the cardiac diseaseby developing heart-specific cDNA arrays [57, 60, 61] or, even more selective, byperforming subtractive hybridization experiments in order to pre-select differentially expressed clones, which were then used to generate cDNA microarrays [56].Once these limitations and problems have been overcome, large scale expressionmonitoring should enhance the development of therapeutic strategies for treatment of cardiac diseases.1.4AcknowledgementsWe thank Pascal Braun, Sekwon Kong, and Jeffrey Brown for critical reading ofthe manuscript, and Ashish Nimgaonkar for help with Fig.
![](https://s.studizba.com/z.php?f=/templates/si/i/noavatar.png&w=100&h=100&t=1"){kind=avatar}
