Non-coding keratin variants associate with liver fibrosis progression in patients with hemochromatosis

Background Keratins 8 and 18 (K8/K18) are intermediate filament proteins that protect the liver from various forms of injury. Exonic K8/K18 variants associate with adverse outcome in acute liver failure and with liver fibrosis progression in patients with chronic hepatitis C infection or primary biliary cirrhosis. Given the association of K8/K18 variants with end-stage liver disease and progression in several chronic liver disorders, we studied the importance of keratin variants in patients with hemochromatosis. Methods The entire K8/K18 exonic regions were analyzed in 162 hemochromatosis patients carrying homozygous C282Y HFE (hemochromatosis gene) mutations. 234 liver-healthy subjects were used as controls. Exonic regions were PCR-amplified and analyzed using denaturing high-performance liquid chromatography and DNA sequencing. Previously-generated transgenic mice overexpressing K8 G62C were studied for their susceptibility to iron overload. Susceptibility to iron toxicity of primary hepatocytes that express K8 wild-type and G62C was also assessed. Results We identified amino-acid-altering keratin heterozygous variants in 10 of 162 hemochromatosis patients (6.2%) and non-coding heterozygous variants in 6 additional patients (3.7%). Two novel K8 variants (Q169E/R275W) were found. K8 R341H was the most common amino-acid altering variant (4 patients), and exclusively associated with an intronic KRT8 IVS7+10delC deletion. Intronic, but not amino-acid-altering variants associated with the development of liver fibrosis. In mice, or ex vivo, the K8 G62C variant did not affect iron-accumulation in response to iron-rich diet or the extent of iron-induced hepatocellular injury. Conclusion In patients with hemochromatosis, intronic but not exonic K8/K18 variants associate with liver fibrosis development.

The mutation causing the black-and-tan pigmentation phenotype of Mangalitza pigs maps to the porcine ASIP locus but does not affect its coding sequence

The gene for agouti signaling protein (ASIP) is centrally involved in the expression of coat color traits in animals. The Mangalitza pig breed is characterized by a black-and-tan phenotype with black dorsal pigmentation and yellow or white ventral pigmentation. We investigated a Mangalitza x Piétrain cross and observed a coat color segregation pattern in the F2 generation that can be explained by virtue of two alleles at the MC1R locus and two alleles at the ASIP locus. Complete linkage of the black-and-tan phenotype to microsatellite alleles at the ASIP locus on SSC 17q21 was observed. Corroborated by the knowledge of similar mouse coat color mutants, it seems therefore conceivable that the black-and-tan pigmentation of Mangalitza pigs is caused by an ASIP allele a(t), which is recessive to the wild-type allele A. Toward positional cloning of the a(t) mutation, a 200-kb genomic BAC/PAC contig of this chromosomal region has been constructed and subsequently sequenced. Full-length ASIP cDNAs obtained by RACE differed in their 5' untranslated regions, whereas they shared a common open reading frame. Comparative sequencing of all ASIP exons and ASIP cDNAs between Mangalitza and Piétrain pigs did not reveal any differences associated with the coat color phenotype. Relative qRT-PCR analyses showed different dorsoventral skin expression intensities of the five ASIP transcripts in black-and-tan Mangalitza. The a(t) mutation is therefore probably a regulatory ASIP mutation that alters its dorsoventral expression pattern.

Distribution of mRNA coding for 5-hydroxytryptamine receptor subtypes in the intestines of healthy dairy cows and dairy cows with cecal dilatation-dislocation

OBJECTIVE: To investigate the distribution of mRNA coding for 7 subtypes of 5-hydroxytryptamine receptors (5-HTRs) in the intestines of healthy dairy cows and dairy cows with cecal dilatation-dislocation (CDD). SAMPLE POPULATION: Full-thickness intestinal wall biopsy specimens were obtained from the ileum, cecum, proximal loop of the ascending colon, and external loop of the spiral colon (ELSC) of 15 cows with CDD (group 1) and 15 healthy dairy cows allocated to 2 control groups (specimens collected during routine laparotomy [group 2] or after cows were slaughtered [group 3]). PROCEDURE: Amounts of mRNA coding for 7 subtypes of 5-HTRs (5-HT1A, 5-HT1B, 5-HT1D, 5-HT1F, 5-HT2A, 5-HT2B, and 5-HT4) were measured by quantitative real-time reverse transcriptase-PCR assay. Results were expressed as the percentage of mRNA expression of a housekeeping gene. RESULTS: Expression of mRNA coding for 5-HTR1B, 5-HTR2B, and 5-HTR4 was significantly lower in cows with CDD than in healthy cows. For 5-HTR2B and 5-HTR4, significant differences between cows with CDD and control cows were most pronounced for the ELSC. Expression of mRNA for 5-HTR1D, 5-HTR1F, and 5-HTR2A was extremely low in all groups, and mRNA for 5-HTR1A was not detected. CONCLUSIONS AND CLINICAL RELEVANCE: Relative concentrations of mRNA coding for 5-HTR1B, 5-HT2B, and 5-HTR4 were significantly lower in the intestines of cows with CDD than in the intestines of healthy dairy cows, especially for 5-HT2B and 5-HTR4 in the ELSC. This supports the hypothesis that serotonergic mechanisms, primarily in the spiral colon, are implicated in the pathogenesis of CDD.

A Fully Bayesian Approach for Combining Multilevel Failure Information in Fault Tree Quantification and Corresponding Optimal Resource Allocation

This paper presents a fully Bayesian approach that simultaneously combines basic event and statistically independent higher event-level failure data in fault tree quantification. Such higher-level data could correspond to train, sub-system or system failure events. The full Bayesian approach also allows the highest-level data that are usually available for existing facilities to be automatically propagated to lower levels. A simple example illustrates the proposed approach. The optimal allocation of resources for collecting additional data from a choice of different level events is also presented. The optimization is achieved using a genetic algorithm.

A MULTILEVEL MODEL TO ADDRESS BATCH EFFECTS IN COPY NUMBER ESTIMATION USING SNP ARRAYS

Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of basepairs across the genome. Genome-wide association studies (GWAS) may simultaneously screen for copy number-phenotype and SNP-phenotype associations as part of the analytic strategy. However, genome-wide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and laboratory equipment. Failure to adjust for batch effects can lead to incorrect inference and requires inefficient post-hoc quality control procedures that exclude regions that are associated with batch. Our work extends previous model-based approaches for copy number estimation by explicitly modeling batch effects and using shrinkage to improve locus-specific estimates of copy number uncertainty. Key features of this approach include the use of diallelic genotype calls from experimental data to estimate batch- and locus-specific parameters of background and signal without the requirement of training data. We illustrate these ideas using a study of bipolar disease and a study of chromosome 21 trisomy. The former has batch effects that dominate much of the observed variation in quantile-normalized intensities, while the latter illustrates the robustness of our approach to datasets where as many as 25% of the samples have altered copy number. Locus-specific estimates of copy number can be plotted on the copy-number scale to investigate mosaicism and guide the choice of appropriate downstream approaches for smoothing the copy number as a function of physical position. The software is open source and implemented in the R package CRLMM available at Bioconductor (http:www.bioconductor.org).

Modeling multilevel sleep transitional data via Poisson log-linear multilevel models

This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed.

ON MARGINALIZED MULTILEVEL MODELS AND THEIR COMPUTATION

Clustered data analysis is characterized by the need to describe both systematic variation in a mean model and cluster-dependent random variation in an association model. Marginalized multilevel models embrace the robustness and interpretations of a marginal mean model, while retaining the likelihood inference capabilities and flexible dependence structures of a conditional association model. Although there has been increasing recognition of the attractiveness of marginalized multilevel models, there has been a gap in their practical application arising from a lack of readily available estimation procedures. We extend the marginalized multilevel model to allow for nonlinear functions in both the mean and association aspects. We then formulate marginal models through conditional specifications to facilitate estimation with mixed model computational solutions already in place. We illustrate this approach on a cerebrovascular deficiency crossover trial.

Multilevel Latent Class Models with Dirichlet Mixing Distribution

Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social sciences and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we develop multilevel latent class model, in which subpopulation mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when either the number of classes or the cluster size is large. We propose a maximum pairwise likelihood (MPL) approach via a modified EM algorithm for this case. We also show that a simple latent class analysis, combined with robust standard errors, provides another consistent, robust, but less efficient inferential procedure. Simulation studies suggest that the three methods work well in finite samples, and that the MPL estimates often enjoy comparable precision as the ML estimates. We apply our methods to the analysis of comorbid symptoms in the Obsessive Compulsive Disorder study. Our models' random effects structure has more straightforward interpretation than those of competing methods, thus should usefully augment tools available for latent class analysis of multilevel data.

Endothelium-specific replacement of the connexin43 coding region by a lacZ reporter gene

The murine gap junction protein connexin43 (Cx43) is expressed in blood vessels, with vastly different contribution by endothelial and smooth muscle cells. We have used the Cre recombinase under control of TIE2 transcriptional elements to inactivate a floxed Cx43 gene specifically in endothelial cells. Cre-mediated deletion led to replacement of the Cx43 coding region by a lacZ reporter gene. This allowed us to monitor the extent of deletion and to visualize the endothelial expression pattern of Cx43. We found widespread endothelial expression of the Cx43 gene during embryonic development, which became restricted largely to capillaries and small vessels in all adult organs examined. Mice lacking Cx43 in endothelium did not exhibit altered blood pressure, in contrast to mice deficient in Cx40. Our results show that lacZ activation after deletion of the target gene allows us to determine the extent of cell type-specific deletion after phenotypical investigation of the same animal.

Comparison of musical activities of cochlear implant users with different speech-coding strategies

Speech coding might have an impact on music perception of cochlear implant users. This questionnaire study compares the musical activities and perception of postlingually deafened cochlear implant users with three different coding strategies (CIS, ACE, SPEAK) using the Munich Music Questionnaire. Overall, the self-reported perception of music of CIS, SPEAK, and ACE users did not differ by very much.

The end1 gene of Schizosaccharomyces pombe coding for a DNase is identical with the pnu1 gene coding for an RNase

The DNA nuclease activity encoded by the end1 gene, and its inactivation by mutation, was described in connection with the characterization of DNA topoisomerases in the fission yeast Schizosaccharomyces pombe (Uemura and Yanagida, 1984). Subsequently, end1 mutant strains were used for the preparation of cell extracts for the study of enzymes and intermediates involved in DNA metabolism. The molecular identification of the end1 gene and its identity with the pnu1 gene is presented. The end1-458 mutation alters glycine to glutamate in the conserved motif TGPYLP. The pnu1 gene codes for an RNase that is induced by nitrogen starvation (Nakashima et al., 2002b). Thus, the End1/Pnu1 protein, like related mitochondrial proteins in other organisms, is an example of a sugar-non-specific nuclease. The analysis of strains carrying a pnu1 deletion revealed no defects in meiotic recombination and spore viability.