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Dr. Jonathan Pevsner is a research scientist at the Kennedy Krieger Institute. He also holds a primary faculty appointment in the Department of Neuroscience at the Johns Hopkins School of Medicine.
Biographical Sketch:
Dr. Pevsner received his bachelor's degree in psychology from Haverford College and his Ph.D. in Pharmacology and Molecular Sciences from the Johns Hopkins School of Medicine. He pursued postdoctoral training at the Stanford University School of Medicine, and joined the faculty of Kennedy Krieger Institute in 1995.
Research Summary:
Dr. Pevsner studies the molecular basis of childhood brain disorders. The diseases we study include autism, Rett Syndrome, Down Syndrome, and lead poisoning. For studies of human brain disorders we perform gene expression profiling to identify disease markers and to search for biochemical pathways that have been disturbed in brain or peripheral cells from patients.
Human exposure to lead (Pb2+), especially at a young age, impairs a range of neurological functions. A blood Pb2+ level above 10 ug/dL is considered potentially hazardous. Recently it has been reported that approximately 5% of children in the U.S. have blood Pb2+ levels greater than or equal to 10 ug/dL. Thus Pb2+ poisoning is one of the most critical environmental health hazards affecting children today. The mechanism of Pb2+ toxicity remains poorly understood. One possible mechanism of its effects may be its influence on synaptic activity. We are studying the molecular basis of lead neurotoxicity in the brain. We have identified the synaptic vesicle protein synaptotagmin as a potential target for lead toxicity in brain. Lead interacts with synaptotogamin at nanomolar concentrations, and may thus alter neurotransmitter release.
The Pevsner Lab is involved in bioinformatics research. Bioinformatics is the interface between molecular biology and computers. The lab has developed the following programs: [1] "Database Referencing of Array Genes ONline" (DRAGON), a web-accessible database that helps researchers analyze the data obtained from microarrays or other gene expression experiments. Once a microarray experiment indicates the expression levels of tens of thousands of genes, researchers must identify the biological characteristics associated with all of those genes and their encoded proteins. Looking on-line for information about each gene individually is time-consuming and impractical. DRAGON compiles information from a variety of public databases. It then rapidly supplies information pertaining to a range of the biological characteristics of the genes in any microarray data set. [2] "Standardization and Normalization of Microarray Data" (SNOMAD), a set of web-accessible tools for the analysis of genes that are significantly regulated in microarray data sets. SNOMAD includes non-linear transformations to correct for bias and variance in array data. [3] "Statistical Analysis and Visualization of Annotated Gene Expression data" (SAVAGE), a data visualization tool that uses principal components analysis to graphically display functionally annotated gene expression data sets.
Recent Publications/Presentations:
Bouton CM, Frelin LP, Forde CE, Godwin HA and Pevsner J. Synaptotagmin is a molecular target for lead. J. Neurochem., 76:1724-35, 2001.
Colantuoni C, Purcell AE, Bouton CM, and Pevsner J. (2000)
High throughput analysis of gene expression in human brain. J. Neurosci. Res. 59:1-10.
Bouton CM, Hossain MA, Frelin LP, Laterra J, Pevsner J. Microarray analysis of differential gene expression in lead-exposed astrocytes. Toxicol Appl Pharmacol 2001 Oct 1;176(1):34-53
Colantuoni C., Zeger S., and Pevsner J. Local mean normalization of microarray element signal intensities across an array surface: quality control and correction of spatically systematic hybridization artifacts. Biotechniques, 32(6):1316-20.
Purcell AE, Jeon OH, Zimmerman AW, Blue ME, Pevsner J. Postmortem brain abnormalities of the glutamate neurotransmitter system in autism. Neurology. 2001 Nov 13;57(9):1618-1628.
Bouton C.M. and Pevsner J. DRAGON View: Information Visualization for Annotated Microarray Data. Bioinformatics, 2002 Feb;18(2):323-4. | 