Biomedical subjects

Lawrence Gelbert

Publications and source records attributed to Lawrence Gelbert.

4 recordsLinked to original sources

PubMed2005

Molecular profile of catabolic versus anabolic treatment regimens of parathyroid hormone (PTH) in rat bone: an analysis by DNA microarray.

Teriparatide, human PTH (1-34), a new therapy for osteoporosis, elicits markedly different skeletal responses depending on the treatment regimen. In order to understand potential mechanisms for this dichotomy, the present investigation utilized microarrays to delineate the genes and pathways that are regulated by intermittent (subcutaneous injection of 80 microg/kg/day) and continuous (subcutaneous infusion of 40 microg/kg/day by osmotic mini pump) PTH (1-34) for 1 week in 6-month-old female rats. The effect of each PTH regimen was confirmed by histomorphometric analysis of the proximal tibial metaphysis, and mRNA from the distal femoral metaphysis was analyzed using an Affymetrix microarray. Both PTH paradigms co-regulated 22 genes including known bone formation genes (i.e., collagens, osteocalcin, decorin, and osteonectin) and also uniquely modulated additional genes. Intermittent PTH regulated 19 additional genes while continuous treatment regulated 173 additional genes. This investigation details for the first time the broad profiling of the gene and pathway changes that occur in vivo following treatment of intermittent versus continuous PTH (1-34). These results extend previous observations of gene expression changes and reveal the in vivo regulation of BMP3 and multiple neuronal genes by PTH treatment.

Animals↗

PubMed2004

At what scale should microarray data be analyzed?

INTRODUCTION: The hybridization intensities derived from microarray experiments, for example Affymetrix's MAS5 signals, are very often transformed in one way or another before statistical models are fitted. The motivation for performing transformation is usually to satisfy the model assumptions such as normality and homogeneity in variance. Generally speaking, two types of strategies are often applied to microarray data depending on the analysis need: correlation analysis where all the gene intensities on the array are considered simultaneously, and gene-by-gene ANOVA where each gene is analyzed individually. AIM: We investigate the distributional properties of the Affymetrix GeneChip signal data under the two scenarios, focusing on the impact of analyzing the data at an inappropriate scale. METHODS: The Box-Cox type of transformation is first investigated for the strategy of pooling genes. The commonly used log-transformation is particularly applied for comparison purposes. For the scenario where analysis is on a gene-by-gene basis, the model assumptions such as normality are explored. The impact of using a wrong scale is illustrated by log-transformation and quartic-root transformation. RESULTS: When all the genes on the array are considered together, the dependent relationship between the expression and its variation level can be satisfactorily removed by Box-Cox transformation. When genes are analyzed individually, the distributional properties of the intensities are shown to be gene dependent. Derivation and simulation show that some loss of power is incurred when a wrong scale is used, but due to the robustness of the t-test, the loss is acceptable when the fold-change is not very large.

Algorithms↗

PubMed2003

Assessing the variability in GeneChip data.

INTRODUCTION: Oligonucleotide and cDNA microarray experiments are now common practice in biological science research. The goal of these experiments is generally to gain clues about the functions of genes by measuring how their expression levels rise and fall in response to changing experimental conditions. Measures of gene expression are affected, however, by a variety of factors. This paper introduces statistical methods to assess the variability of Affymetrix GeneChip data due to randomness. METHODS: The variation of Affymetrix's GeneChip signal data are quantified at both chip level and individual gene level, respectively, by the agreement study method and variance components method. Three agreement measurement methods are introduced to assess the variability among chips. Variation sources for gene expression data are decomposed into four categories: systematic experiment variation, treatment effect, biological variation, and chip variation. The focus of this paper is on evaluating and comparing the last two kinds of variations. RESULTS: Measurement of agreement and variance components methods were applied to an experimental data, and the calculation and interpretation were exemplified. The variability between biological samples were shown to exist and were assessed at both the chip level and individual gene level. Using the variance components method, it was found that the biological and chip variation are roughly comparable. The Statistical Analysis System (SAS) program for doing the agreement studies can be obtained from the correspondence author.

Algorithms↗

PubMed2002

Aldosterone stimulates angiotensin-converting enzyme expression and activity in rat neonatal cardiac myocytes.

BACKGROUND: Members of the nuclear receptor family proteins function as transcription factors upon ligand binding and thereby regulate gene expression in host cells. Aldosterone, the high-affinity endogenous ligand for the mineralocorticoid receptor, induces cardiac hypertrophy and fibrosis in a variety of animal models, but the transcriptional targets for aldosterone in the myocardium are not well-described. METHODS AND RESULTS: Using quantitative reverse transcription-polymerase chain reaction method, we show that in cultured rat neonatal cardiomyocytes, aldosterone stimulates expression of angiotensin converting enzyme (ACE) in a concentration and time-dependent manner. Aldosterone (50 and 100 nM) increased levels of ACE mRNA by 1.8- and 2.2-fold, respectively. Aldosterone-induced ACE gene expression was blocked by spironolactone (1 microM), a mineralocorticoid receptor antagonist. In contrast, the expressions of the type I angiotensin receptor was not induced by aldosterone in either cardiac myocytes or fibroblasts. Consistent with the increased ACE mRNA level, 100 nM aldosterone also induced a 2-fold increase in ACE activity in cardiac myocytes. CONCLUSION: ACE gene expression may be a target for mineralocorticoid receptors in the myocardium, supporting the notion that at least some of the known adverse effects of aldosterone on the myocardium are mediated by increased angiotensin II.

Aldosterone↗