292 research outputs found

    A Growth Curve Model with Fractional Polynomials for Analysing Incomplete Time-Course Data in Microarray Gene Expression Studies

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    Identifying the various gene expression response patterns is a challenging issue in expression microarray time-course experiments. Due to heterogeneity in the regulatory reaction among thousands of genes tested, it is impossible to manually characterize a parametric form for each of the time-course pattern in a gene by gene manner. We introduce a growth curve model with fractional polynomials to automatically capture the various time-dependent expression patterns and meanwhile efficiently handle missing values due to incomplete observations. For each gene, our procedure compares the performances among fractional polynomial models with power terms from a set of fixed values that offer a wide range of curve shapes and suggests a best fitting model. After a limited simulation study, the model has been applied to our human in vivo irritated epidermis data with missing observations to investigate time-dependent transcriptional responses to a chemical irritant. Our method was able to identify the various nonlinear time-course expression trajectories. The integration of growth curves with fractional polynomials provides a flexible way to model different time-course patterns together with model selection and significant gene identification strategies that can be applied in microarray-based time-course gene expression experiments with missing observations

    Genetic and environmental determinants of O6-methylguanine DNA-methyltransferase (MGMT) gene methylation: a 10-year longitudinal study of Danish twins

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    Background: Epigenetic inactivation of O6-methylguanine DNA-methyltransferase (MGMT) is associated with increased sensitivity to alkylating chemotherapeutic agents in glioblastoma patients. The genetic background underlying MGMT gene methylation may explain individual differences in treatment response and provide a clue to a personalized treatment strategy. Making use of the longitudinal twin design, we aimed, for the first time, to estimate the genetic contributions to MGMT methylation in a Danish twin cohort. Methods: DNA-methylation from whole blood (18 monozygotic (MZ) and 25 dizygotic (DZ) twin pairs) repeated 10 years apart from the Longitudinal Study of Aging Danish Twins (LSADT) were used to search for genetic and environmental contributions to DNA-methylation at 170 CpG sites of across the MGMT gene. Both univariate and bivariate twin models were applied. The intraclass correlations, performed on cross-sectional data (246 MZ twin pairs) from an independent study population, the Middle-Aged Danish Twins (MADT), were used to assess the genetic influence at each CpG site of MGMT for replication. Results: Univariate twin model revealed twelve CpG sites showing significantly high heritability at intake (wave 1, h2 > 0.43), and seven CpG sites with significant heritability estimates at end of follow-up (wave 2, h2 > 0.5). There were six significant CpG sites, located at the gene body region, that overlapped among the two waves (h2 > 0.5), of which five remained significant in the bivariate twin model, which was applied to both waves. Within MZ pair correlation in these six CpGs from MADT demarks top level of genetic influence. There were 11 CpGs constantly have substantial common environmental component over the 10 years. Conclusions: We have identified 6 CpG sites linked to the MGMT gene with strong and persistent genetic control based on their DNA methylation levels. The genetic basis of MGMT gene methylation could help to explain individual differences in glioblastoma treatment response and most importantly, provide references for mapping the methylation Quantitative Trait Loci (meQTL) underlying the genetic regulation.Peer reviewe

    Lithological anomalies in a relict coastal dune : geophysical and paleoenvironmental markers

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    Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 34 (2007): L09707, doi:10.1029/2007GL029767.Ground exposures of migration surfaces (slipfaces) of a relict Holocene coastal dune along the southeastern Baltic Sea coast provide an ideal opportunity for establishing the causes of prominent reflections on geophysical profiles. High-amplitude reflections on high-resolution ground-penetrating radar (GPR) images correlate well with two major lithological anomalies: 1) paleosols developed on dune slipfaces, and 2) slipfaces consisting of heavy-mineral concentrations (HMCs). Paleosols serve as indicators of dune stability, represent datable chronostratigraphic surfaces, and help reconstruct dune paleo-morphology. HMCs have substantially higher magnetic susceptibility values than background quartz-rich sands and, where they are well-developed, can be also used for spatial correlation. Based on their occurrence at the study site, these enriched horizons likely represent periods of increased wind activity (storminess). Multiple HMCs upwind of paleosol P1 (800–670 cal years BP) likely reflect periods of intensified wind activity along the southeast Baltic region during the Medieval Warm Period.This research was funded by the Ocean and Climate Change Institute and The J. Lamar Worzel Assistant Scientist Fund of the Woods Hole Oceanographic Institution
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