Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases.     

Hierarchical trees can be perfectly scaled in one dimension

Holman (1972) proved theorems which led him to suggest that there was a fundamental opposition between hierarchical clustering and non-metric Euclidean multidimensional scaling. Empirical experience has shown this to be untrue. Explanations of this apparent contradiction have been offered previously by Kruskal (1977) and Critchley (1986). In this paper we point out the feasibility of perfectly scaling a hierarchical tree in one dimension when the primary approach to ties (Kruskal 1964) is taken. Indeed, there is a whole polyhedral convex cone of solutions for which we obtain an explicit expression.     

Cluster Differences Unfolding for Two-Way Two-Mode Preference Rating Data

Classification and spatial methods can be used in conjunction to represent the individual information of similar preferences by means of groups. In the context of latent class models and using Simulated Annealing, the cluster-unfolding model for two-way two-mode preference rating data has been shown to be superior to a two-step approach of first deriving the clusters and then unfolding the classes. However, the high computational cost makes the procedure only suitable for small or medium-sized data sets, and the hypothesis of independent and normally distributed preference data may also be too restrictive in many practical situations. Therefore, an alternating least squares procedure is proposed, in which the individuals and the objects are partitioned into clusters, while at the same time the cluster centers are represented by unfolding. An enhanced Simulated Annealing algorithm in the least squares framework is also proposed in order to address the local optimum problem. Real and artificial data sets are analyzed to illustrate the performance of the model.     

Mouse models for human intestinal microbiota research: a critical evaluation

Since the early days of the intestinal microbiota research, mouse models have been used frequently to study the interaction of microbes with their host. However, to translate the knowledge gained from mouse studies to a human situation, the major spatio-temporal similarities and differences between intestinal microbiota in mice and humans need to be considered. This is done here with specific attention for the comparative physiology of the intestinal tract, the effect of dietary patterns and differences in genetics. Detailed phylogenetic and metagenomic analysis showed that while many common genera are found in the human and murine intestine, these differ strongly in abundance and in total only 4% of the bacterial genes are found to share considerable identity. Moreover, a large variety of murine strains is available yet most of the microbiota research is performed in wild-type, inbred strains and their transgenic derivatives. It has become increasingly clear that the providers, rearing facilities and the genetic background of these mice have a significant impact on the microbial composition and this is illustrated with recent experimental data. This may affect the reproducibility of mouse microbiota studies and their conclusions. Hence, future studies should take these into account to truly show the effect of diet, genotype or environmental factors on the microbial composition.     

Tbx2 and Tbx3 induce atrioventricular myocardial development and endocardial cushion formation

A key step in heart development is the coordinated development of the atrioventricular canal (AVC), the constriction between the atria and ventricles that electrically and physically separates the chambers, and the development of the atrioventricular valves that ensure unidirectional blood flow. Using knock-out and inducible overexpression mouse models, we provide evidence that the developmentally important T-box factors Tbx2 and Tbx3, in a functionally redundant manner, maintain the AVC myocardium phenotype during the process of chamber differentiation. Expression profiling and ChIP-sequencing analysis of Tbx3 revealed that it directly interacts with and represses chamber myocardial genes, and induces the atrioventricular pacemaker-like phenotype by activating relevant genes. Moreover, mutant mice lacking 3 or 4 functional alleles of Tbx2 and Tbx3 failed to form atrioventricular cushions, precursors of the valves and septa. Tbx2 and Tbx3 trigger development of the cushions through a regulatory feed-forward loop with Bmp2, thus providing a mechanism for the co-localization and coordination of these important processes in heart development.