Historical HbA Values May Explain the Type 2 Diabetes Legacy Effect: UKPDS 88.

Objective: Type 2 diabetes all-cause mortality (ACM) and myocardial infarction (MI) glycemic legacy effects have not been explained. We examined their relationships with prior individual HbA values and explored the potential impact of instituting earlier, compared with delayed, glucose-lowering therapy.

Research Design And Methods: Twenty-year ACM and MI hazard functions were estimated from diagnosis of type 2 diabetes in 3,802 UK Prospective Diabetes Study participants.

Modelling of zero-inflation improves inference of metagenomic gene count data.

Metagenomics enables the study of gene abundances in complex mixtures of microorganisms and has become a standard methodology for the analysis of the human microbiome. However, gene abundance data is inherently noisy and contains high levels of biological and technical variability as well as an excess of zeros due to non-detected genes. This makes the statistical analysis challenging.

Searching for neurodegeneration in multiple sclerosis at clinical onset: Diagnostic value of biomarkers.

Background: Neurodegeneration occurs during the early stages of multiple sclerosis. It is an essential, devastating part of the pathophysiology. Tools for measuring the degree of neurodegeneration could improve diagnostics and patient characterization.

Variability in Metagenomic Count Data and Its Influence on the Identification of Differentially Abundant Genes.

Metagenomics is the study of microorganisms in environmental and clinical samples using high-throughput sequencing of random fragments of their DNA. Since metagenomics does not require any prior culturing of isolates, entire microbial communities can be studied directly in their natural state. In metagenomics, the abundance of genes is quantified by sorting and counting the DNA fragments.

Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics.

Background: Metagenomics is the study of microbial communities by sequencing of genetic material directly from environmental or clinical samples. The genes present in the metagenomes are quantified by annotating and counting the generated DNA fragments. Identification of differentially abundant genes between metagenomes can provide important information about differences in community structure, diversity and biological function.

Upper Respiratory Infections and MRI Activity in Relapsing-Remitting Multiple Sclerosis.

Background: Although clinical reports have suggested a relationship between systemic infections and multiple sclerosis (MS) relapses, MRI evidence supporting an association is conflicting. Here we evaluated the temporal relationship between upper respiratory infections (URIs) and MRI activity in relapsing-remitting (RR) MS.

Methods: We combined individual data on URI with data on active lesions in pre-scheduled MRI examinations performed every 4 weeks for 28 weeks in 69 patients.

The outcome spectrum of multiple sclerosis: disability, mortality, and a cluster of predictors from onset.

Interest in the long-term natural history of multiple sclerosis (MS) is being revived, as disability endpoints become increasingly important with the advent of highly efficacious long range but potentially harmful drugs. MS had an increasingly benign course, probably due to better assessment and changing diagnostic criteria. Incidence cohorts reduce inclusion bias, capturing both extreme benign and severe cases.

Sleep apnea-related risk of motor vehicle accidents is reduced by continuous positive airway pressure: Swedish Traffic Accident Registry data.

Study Objectives: Obstructive sleep apnea (OSA) is associated with an increased risk of motor vehicle accidents (MVAs). The rate of MVAs in patients suspected of having OSA was determined and the effect of continuous positive airway pressure (CPAP) was investigated.

Design: MVA rate in patients referred for OSA was compared to the rate in the general population using data from the Swedish Traffic Accident Registry (STRADA), stratified for age and calendar year.

The association between HbA1c, fasting glucose, 1-hour glucose and 2-hour glucose during an oral glucose tolerance test and cardiovascular disease in individuals with elevated risk for diabetes.

Objective: To determine the association between HbA1c, fasting plasma glucose (FPG), 1-hour (1 hPG) and 2-hour (2 hPG) glucose after an oral glucose tolerance test (OGTT) and cardiovascular disease in individuals with elevated risk for diabetes.

Design: We studied the relationship between baseline, updated mean and updated (last) value of HbA1c, FPG, 1 hPG and 2 hPG after an oral 75 g glucose tolerance test (OGTT) and acute CVD events in 504 individuals with impaired glucose tolerance (IGT) at baseline enrolled in the Finnish Diabetes Prevention Study.

Setting: Follow-up of clinical trial.

Changes in HbA1c and frequency of measuring HbA1c and adjusting glucose-lowering medications in the 10 years following diagnosis of type 2 diabetes: a population-based study in the UK.

Aims/hypothesis: The aim of this work was to study levels of HbA1c and patterns of adjusting glucose-lowering drugs in patients with impaired glycaemic control over 10 years after diagnosis of type 2 diabetes.

Methods: We studied 4,529 individuals in The Health Improvement Network Database newly diagnosed with type 2 diabetes in the year 2000.

Results: From 6 months to 10 years after diagnosis, the HbA1c increased from 7.

A novel method for cross-species gene expression analysis.

Background: Analysis of gene expression from different species is a powerful way to identify evolutionarily conserved transcriptional responses. However, due to evolutionary events such as gene duplication, there is no one-to-one correspondence between genes from different species which makes comparison of their expression profiles complex.

Results: In this paper we describe a new method for cross-species meta-analysis of gene expression.

Transcriptional and metabolic data integration and modeling for identification of active pathways.

With the growing availability of omics data generated to describe different cells and tissues, the modeling and interpretation of such data has become increasingly important. Pathways are sets of reactions involving genes, metabolites, and proteins highlighting functional modules in the cell. Therefore, to discover activated or perturbed pathways when comparing two conditions, for example two different tissues, it is beneficial to use several types of omics data.

Distinct cytoplasmic and nuclear functions of the stress induced protein DDIT3/CHOP/GADD153.

DDIT3, also known as GADD153 or CHOP, encodes a basic leucine zipper transcription factor of the dimer forming C/EBP family. DDIT3 is known as a key regulator of cellular stress response, but its target genes and functions are not well characterized. Here, we applied a genome wide microarray based expression analysis to identify DDIT3 target genes and functions.

Expression profiling of GIST: CD133 is associated with KIT exon 11 mutations, gastric location and poor prognosis.

In gastrointestinal stromal tumors (GISTs), KIT exon 11 deletions are associated with poor prognosis. The aim of this study was to determine the gene expression profiles of GISTs carrying KIT exon 11 deletions and to identify genes associated with poor prognosis. Expression profiling was performed on nine tumors with KIT exon 11 deletions and 7 without KIT exon 11 mutations using oligonucleotide microarrays.

Testing of chromosomal clumping of gene properties.

Clumping of gene properties like expression or mutant phenotypes along chromosomes is commonly detected using completely random null-models where their location is equally likely across the chromosomes. Interpretation of statistical tests based on these assumptions may be misleading if dependencies exist that are unequal between chromosomes or in different chromosomal parts. One such regional dependency is the telomeric effect, observed in several studies of Saccharomyces cerevisiae, under which e.

Genetic basis of arsenite and cadmium tolerance in Saccharomyces cerevisiae.

Background: Arsenic and cadmium are widely distributed in nature and pose serious threats to the environment and human health. Exposure to these nonessential toxic metals may result in a variety of human diseases including cancer. However, arsenic and cadmium toxicity targets and the cellular systems contributing to tolerance acquisition are not fully known.

Evolutionary forces act on promoter length: identification of enriched cis-regulatory elements.

Transcription factors govern gene expression by binding to short DNA sequences called cis-regulatory elements. These sequences are typically located in promoters, which are regions of variable length upstream of the open reading frames of genes. Here, we report that promoter length and gene function are related in yeast, fungi, and plants.

mRNA stability changes precede changes in steady-state mRNA amounts during hyperosmotic stress.

Under stress, cells need to optimize the activity of a wide range of gene products during the response phases: shock, adaptation, and recovery. This requires coordination of several levels of regulation, including turnover and translation efficiencies of mRNAs. Mitogen-activated protein (MAP) kinase pathways are implicated in many aspects of the environmental stress response, including initiation of transcription, translation efficiency, and mRNA turnover.

Evolutionary conservation of human drug targets in organisms used for environmental risk assessments.

Pharmaceuticals are typically found in very low concentrations in the aquatic environment. Accordingly, environmental effects clearly assigned to residual drugs are consistent with high affinity interactions with conserved targets in affected wildlife species rather than with a general toxic effect. Thus, evolutionarily well-conserved targets in a given species are associated with an increased risk.

Weighted analysis of general microarray experiments.

Background: In DNA microarray experiments, measurements from different biological samples are often assumed to be independent and to have identical variance. For many datasets these assumptions have been shown to be invalid and typically lead to too optimistic p-values. A method called WAME has been proposed where a variance is estimated for each sample and a covariance is estimated for each pair of samples.

Sensitive and robust gene expression changes in fish exposed to estrogen--a microarray approach.

Background: Vitellogenin is a well established biomarker for estrogenic exposure in fish. However, effects on gonadal differentiation at concentrations of estrogen not sufficient to give rise to a measurable vitellogenin response suggest that more sensitive biomarkers would be useful. Induction of zona pellucida genes may be more sensitive but their specificities are not as clear.

Quantitative transcriptome, proteome, and sulfur metabolite profiling of the Saccharomyces cerevisiae response to arsenite.

Arsenic is ubiquitously present in nature, and various mechanisms have evolved enabling cells to evade toxicity and acquire tolerance. Herein, we explored how Saccharomyces cerevisiae (budding yeast) respond to trivalent arsenic (arsenite) by quantitative transcriptome, proteome, and sulfur metabolite profiling. Arsenite exposure affected transcription of genes encoding functions related to protein biosynthesis, arsenic detoxification, oxidative stress defense, redox maintenance, and proteolytic activity.

PROPHECY--a yeast phenome database, update 2006.

Connecting genotype to phenotype is fundamental in biomedical research and in our understanding of disease. Phenomics--the large-scale quantitative phenotypic analysis of genotypes on a genome-wide scale--connects automated data generation with the development of novel tools for phenotype data integration, mining and visualization. Our yeast phenomics database PROPHECY is available at http://prophecy.

Quality optimised analysis of general paired microarray experiments.

In microarray experiments, several steps may cause sub-optimal quality and the need for quality control is strong. Often the experiments are complex, with several conditions studied simultaneously. A linear model for paired microarray experiments is proposed as a generalisation of the paired two-sample method by Kristiansson et al.