The winter peak in the occurrence of acute aortic dissection is independent of climate

We recently reported the existence of a higher risk of acute aortic dissection (AAD) during the winter months. However, it is not known whether this winter peak is affected by climate. To address this issue, we evaluated data from 969 AAD patients who were enrolled at various sites around the globe and who were participating in the International Registry of Acute Aortic Dissection (IRAD). We found a significant (p=0.001; χ² test) difference in the number of AAD events occurring during the different seasons of the year, with highest incidence in winter (28.4%) and lowest incidence in summer (19.9%). Furthermore, the winter peak was evident in both cold and temperate climate settings, suggesting that the relative change in temperature, rather than absolute temperature, and/or endogenous annual rhythms are critical mechanistic factors.     

Clarification of the nomenclature for MSC: The International Society for Cellular Therapy position statement

The plastic-adherent cells isolated from BM and other sources have come to be widely known as mesenchymal stem cells (MSC). However, the recognized biologic properties of the unfractionated population of cells do not seem to meet generally accepted criteria for stem cell activity, rendering the name scientifically inaccurate and potentially misleading to the lay public. Nonetheless, a bona fide MSC most certainly exists. To address this inconsistency between nomenclature and biologic properties, and to clarify the terminology, we suggest that the fibroblast-like plastic-adherent cells, regardless of the tissue from which they are isolated, be termed multipotent mesenchymal stromal cells, while the term mesenchymal stem cells is used only for cells that meet specified stem cell criteria. The widely recognized acronym, MSC, may be used for both cell populations, as is the current practice; thus, investigators must clearly define the more scientifically correct designation in their reports. The International Society for Cellular Therapy (ISCT) encourages the scientific community to adopt this uniform nomenclature in all written and oral communications.     

Candidate-gene screening and association analysis at the autism-susceptibility locus on chromosome 16p: evidence of association at GRIN2A and ABAT

Autism is a highly heritable neurodevelopmental disorder whose underlying genetic causes have yet to be identified. To date, there have been eight genome screens for autism, two of which identified a putative susceptibility locus on chromosome 16p. In the present study, 10 positional candidate genes that map to 16p11-13 were examined for coding variants: A2BP1, ABAT, BFAR, CREBBP, EMP2, GRIN2A, MRTF-B, SSTR5, TBX6, and UBN1. Screening of all coding and regulatory regions by denaturing high-performance liquid chromatography identified seven nonsynonymous changes. Five of these mutations were found to cosegregate with autism, but the mutations are not predicted to have deleterious effects on protein structure and are unlikely to represent significant etiological variants. Selected variants from candidate genes were genotyped in the entire International Molecular Genetics Study of Autism Consortium collection of 239 multiplex families and were tested for association with autism by use of the pedigree disequilibrium test. Additionally, genotype frequencies were compared between 239 unrelated affected individuals and 192 controls. Patterns of linkage disequilibrium were investigated, and the transmission of haplotypes across candidate genes was tested for association. Evidence of single-marker association was found for variants in ABAT, CREBBP, and GRIN2A. Within these genes, 12 single-nucleotide polymorphisms (SNPs) were subsequently genotyped in 91 autism trios (one affected individual and two unaffected parents), and the association was replicated within GRIN2A (Fisher's exact test, P<.0001). Logistic regression analysis of SNP data across GRIN2A and ABAT showed a trend toward haplotypic differences between cases and controls.     

In-depth metabolic phenotyping of genetically engineered mouse models in obesity and diabetes

The world-wide prevalence of obesity and diabetes has increased sharply during the last two decades. Accordingly, the metabolic phenotyping of genetically engineered mouse models is critical for evaluating the functional roles of target genes in obesity and diabetes, and for developing new therapeutic targets. In this review, we discuss the practical meaning of metabolic phenotyping, the strategy of choosing appropriate tests, and considerations when designing and performing metabolic phenotyping in mice.     

Characterization of polyploid wheat genomic diversity using a high‐density 90 000 single nucleotide polymorphism array

High‐density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene‐associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome‐wide distributed SNPs that are represented in populations of diverse geographical origin. We used density‐based spatial clustering algorithms to enable high‐throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model‐free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low‐intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.     

Integrated genetic and epigenetic analysis identifies haplotype-specific methylation in the FTO type 2 diabetes and obesity susceptibility locus

Recent multi-dimensional approaches to the study of complex disease have revealed powerful insights into how genetic and epigenetic factors may underlie their aetiopathogenesis. We examined genotype-epigenotype interactions in the context of Type 2 Diabetes (T2D), focussing on known regions of genomic susceptibility. We assayed DNA methylation in 60 females, stratified according to disease susceptibility haplotype using previously identified association loci. CpG methylation was assessed using methylated DNA immunoprecipitation on a targeted array (MeDIP-chip) and absolute methylation values were estimated using a Bayesian algorithm (BATMAN). Absolute methylation levels were quantified across LD blocks, and we identified increased DNA methylation on the FTO obesity susceptibility haplotype, tagged by the rs8050136 risk allele A (p = 9.40×10⁻⁴, permutation p = 1.0×10⁻³). Further analysis across the 46 kb LD block using sliding windows localised the most significant difference to be within a 7.7 kb region (p = 1.13×10⁻⁷). Sequence level analysis, followed by pyrosequencing validation, revealed that the methylation difference was driven by the co-ordinated phase of CpG-creating SNPs across the risk haplotype. This 7.7 kb region of haplotype-specific methylation (HSM), encapsulates a Highly Conserved Non-Coding Element (HCNE) that has previously been validated as a long-range enhancer, supported by the histone H3K4me1 enhancer signature. This study demonstrates that integration of Genome-Wide Association (GWA) SNP and epigenomic DNA methylation data can identify potential novel genotype-epigenotype interactions within disease-associated loci, thus providing a novel route to aid unravelling common complex diseases.