Biomedical subjects

Bryan C Frank

Publications and source records attributed to Bryan C Frank.

8 recordsLinked to original sources

PubMed2006

Gene expression profiling of lymphoblastoid cell lines from monozygotic twins discordant in severity of autism reveals differential regulation of neurologically relevant genes.

BACKGROUND: The autism spectrum encompasses a set of complex multigenic developmental disorders that severely impact the development of language, non-verbal communication, and social skills, and are associated with odd, stereotyped, repetitive behavior and restricted interests. To date, diagnosis of these neurologically based disorders relies predominantly upon behavioral observations often prompted by delayed speech or aberrant behavior, and there are no known genes that can serve as definitive biomarkers for the disorders. RESULTS: Here we demonstrate, for the first time, that lymphoblastoid cell lines from monozygotic twins discordant with respect to severity of autism and/or language impairment exhibit differential gene expression patterns on DNA microarrays. Furthermore, we show that genes important to the development, structure, and/or function of the nervous system are among the most differentially expressed genes, and that many of these genes map closely in silico to chromosomal regions containing previously reported autism candidate genes or quantitative trait loci. CONCLUSION: Our results provide evidence that novel candidate genes for autism may be differentially expressed in lymphoid cell lines from individuals with autism spectrum disorders. This finding further suggests the possibility of developing a molecular screen for autism based on expressed biomarkers in peripheral blood lymphocytes, an easily accessible tissue. In addition, gene networks are identified that may play a role in the pathophysiology of autism.

Autistic Disorder↗

PubMed2006

Combined application of behavior genetics and microarray analysis to identify regional expression themes and gene-behavior associations.

In this report we link candidate genes to complex behavioral phenotypes by using a behavior genetics approach. Gene expression signatures were generated for the prefrontal cortex, ventral striatum, temporal lobe, periaqueductal gray, and cerebellum in eight inbred strains from priority group A of the Mouse Phenome Project. Bioinformatic analysis of regionally enriched genes that were conserved across all strains revealed both functional and structural specialization of particular brain regions. For example, genes encoding proteins with demonstrated anti-apoptotic function were over-represented in the cerebellum, whereas genes coding for proteins associated with learning and memory were enriched in the ventral striatum, as defined by the Expression Analysis Systematic Explorer (EASE) application. Association of regional gene expression with behavioral phenotypes was exploited to identify candidate behavioral genes. Phenotypes that were investigated included anxiety, drug-naive and ethanol-induced distance traveled across a grid floor, and seizure susceptibility. Several genes within the glutamatergic signaling pathway (i.e., NMDA/glutamate receptor subunit 2C, calmodulin, solute carrier family 1 member 2, and glutamine synthetase) were identified in a phenotype-dependent and region-specific manner. In addition to supporting evidence in the literature, many of the genes that were identified could be mapped in silico to surrogate behavior-related quantitative trait loci. The approaches and data set described herein serve as a valuable resource to investigate the genetic underpinning of complex behaviors.

Alcoholism↗

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

Independence and reproducibility across microarray platforms.

Microarrays have been widely used for the analysis of gene expression, but the issue of reproducibility across platforms has yet to be fully resolved. To address this apparent problem, we compared gene expression between two microarray platforms: the short oligonucleotide Affymetrix Mouse Genome 430 2.0 GeneChip and a spotted cDNA array using a mouse model of angiotensin II-induced hypertension. RNA extracted from treated mice was analyzed using Affymetrix and cDNA platforms and then by quantitative RT-PCR (qRT-PCR) for validation of specific genes. For the 11,710 genes present on both arrays, we assessed the relative impact of experimental treatment and platform on measured expression and found that biological treatment had a far greater impact on measured expression than did platform for more than 90% of genes, a result validated by qRT-PCR. In the small number of cases in which platforms yielded discrepant results, qRT-PCR generally did not confirm either set of data, suggesting that sequence-specific effects may make expression predictions difficult to make using any technique.

Angiotensin II↗

PubMed2005

Iterative microarray and RNA interference-based interrogation of the SRC-induced invasive phenotype.

Src kinase has long been recognized as a factor in the progression of colorectal cancer and seems to play a specific role in the development of the metastatic phenotype. In spite of numerous studies conducted to elucidate the exact role of Src in cancer progression, downstream targets of Src remain poorly understood. Gene expression profiling has permitted the identification of large sets of genes that may be functionally interrelated but it is often unclear as to which molecular pathways they belong. Here we have developed an iterative approach to experimentally reconstruct a network of gene activity regulated by Src and contributing to the invasive phenotype. Our strategy uses a combination of phenotypic anchoring of gene expression profiles and loss-of-function screening by way of RNA-mediated interference. Using a panel of human colon cancer cell lines exhibiting differential Src-specific activity and invasivity, we identify the first two levels of gene transcription responsible for the invasive phenotype, where first-tier genes are controlled by Src activity and the second-tier genes are under the influence of the first tier. Specifically, perturbation of first-tier gene activity by either pharmacologic inhibition of Src or RNA-mediated interference-directed knockdown leads to a loss of invasivity and decline of second-tier gene activity. The targeting of first-tier genes may be bypassed altogether because knockdown of second-tier genes led to a similar loss of invasive potential. In this manner, numerous members of a "transcriptional cascade" pathway for metastatic activity have been identified and functionally validated.

Biomarkers, Tumor↗

PubMed2004

Cardiac transcriptional response to acute and chronic angiotensin II treatments.

Exposure of experimental animals to increased angiotensin II (ANG II) induces hypertension associated with cardiac hypertrophy, inflammation, and myocardial necrosis and fibrosis. Some of the most effective antihypertensive treatments are those that antagonize ANG II. We investigated cardiac gene expression in response to acute (24 h) and chronic (14 day) infusion of ANG II in mice; 24-h treatment induces hypertension, and 14-day treatment induces hypertension and extensive cardiac hypertrophy and necrosis. For genes differentially expressed in response to ANG II treatment, we tested for significant regulation of pathways, based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Microarray Pathway Profiler (GenMAPP) databases, as well as functional classes based on Gene Ontology (GO) terms. Both acute and chronic ANG II treatments resulted in decreased expression of mitochondrial metabolic genes, notably those for the electron transport chain and Krebs-TCA cycle; chronic ANG II treatment also resulted in decreased expression of genes involved in fatty acid metabolism. In contrast, genes involved in protein translation and ribosomal activity increased expression following both acute and chronic ANG II treatments. Some classes of genes showed differential response between acute and chronic ANG II treatments. Acute treatment increased expression of genes involved in oxidative stress and amino acid metabolism, whereas chronic treatments increased cytoskeletal and extracellular matrix genes, second messenger cascades responsive to ANG II, and amyloidosis genes. Although a functional linkage between Alzheimer disease, hypertension, and high cholesterol has been previously documented in studies of brain tissue, this is the first demonstration of induction of Alzheimer disease pathways by hypertension in heart tissue. This study provides the most comprehensive available survey of gene expression changes in response to acute and chronic ANG II treatment, verifying results from disparate studies, and suggests mechanisms that provide novel insight into the etiology of hypertensive heart disease and possible therapeutic interventions that may help to mitigate its effects.

Angiotensin II↗

PubMed2004

Genetic regulation of endotoxin-induced airway disease.

To identify novel genes regulating the biologic response to lipopolysaccharide (LPS), we used a combination of quantitative trait locus (QTL) analysis and microarray-based gene expression studies of C57BL/6J x DBA/2J(BXD) F2 and recombinant inbred (RI) mice. A QTL affecting pulmonary TNF-alpha production was identified on chromosome 2, and a region affecting both polymorphonuclear leukocyte recruitment and TNF-alpha levels was identified on chromosome 11. Microarray analyses of unchallenged and LPS-challenged BXD RI strains identified approximately 500 genes whose expression was significantly changed by inhalation of LPS. Of these genes, 28 reside within the chromosomal regions identified by the QTL analyses, implicating these genes as high priority candidates for functional studies. Additional high priority candidate genes were identified based on their differential expression in mice having high and low responses to LPS. Functional studies of these genes are expected to reveal important molecular mechanisms regulating the magnitude of biologic responses to LPS.

Animals↗

PubMed2002

Within the fold: assessing differential expression measures and reproducibility in microarray assays.

BACKGROUND: 'Fold-change' cutoffs have been widely used in microarray assays to identify genes that are differentially expressed between query and reference samples. More accurate measures of differential expression and effective data-normalization strategies are required to identify high-confidence sets of genes with biologically meaningful changes in transcription. Further, the analysis of a large number of expression profiles is facilitated by a common reference sample, the construction of which must be carefully addressed. RESULTS: We carried out a series of 'self-self' hybridizations in which aliquots of the same RNA sample were labeled separately with Cy3 and Cy5 fluorescent dyes and co-hybridized to the same microarray. From this, we can analyze the intensity-dependent behavior of microarray data, define a statistically significant measure of differential expression that exploits the structure of the fluorescent signals, and measure the inherent reproducibility of the technique. We also devised a simple procedure for identifying and eliminating low-quality data for replicates within and between slides. We examine the properties required of a universal reference RNA sample and show how pooling a small number of samples with a diverse representation of expressed genes can outperform more complex mixtures as a reference sample. CONCLUSION: Analysis of cell-line samples can identify systematic structure in measured gene-expression levels. A general procedure for analyzing cDNA microarray data is proposed and validated. We show that pooled reference samples should be based not only on the expression of individual genes in each cell line but also on the expression levels of genes within cell lines.

Brain Neoplasms↗