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Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n= 35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (padj= 6.73 × 10−6). Novel reciprocal case–control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to the deletion conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present.

In their article in this issue of ONCOLOGY, Drs. Ma and Ellis report on the clinical implications of The Cancer Genome Atlas (TCGA) project for breast cancer, [1] a collaborative [...]

The cytoskeletal interacting protein Septin 9 (SEPT9), a member of the septin gene family, has been proposed to have oncogenic functions. It is a known hot spot of retroviral tagging insertion and a fusion partner of both de novo and therapy-induced mixed lineage leukemia (MLL). Of all septins, SEPT9holds the strongest link to cancer, especially breast cancer. Murine models of breast cancer frequently exhibit SEPT9amplification in the form of double minute chromosomes, and about 20% of human breast cancer display genomic amplification and protein over expression at the SEPT9locus. Yet, a clear mechanism by which SEPT9elicits tumor-promoting functions is lacking. To obtain unbiased insights on molecular signatures of SEPT9upregulation in breast tumors, we overexpressed several of its isoforms in breast cancer cell lines. Global transcriptomic profiling supports a role of SEPT9in invasion. Functional studies reveal that SEPT9upregulation is sufficient to increase degradation of the extracellular matrix, while SEPT9downregulation inhibits this process. The degradation pattern is peripheral and associated with focal adhesions (FAs), where it is coupled with increased expression of matrix metalloproteinases (MMPs). SEPT9overexpression induces MMP upregulation in human tumors and in culture models and promotes MMP3 secretion to the media at FAs. Downregulation of SEPT9or chemical inhibition of septin filament assembly impairs recruitment of MMP3 to FAs. Our results indicate that SEPT9 promotes upregulation and both trafficking and secretion of MMPs near FAs, thus enhancing migration and invasion of breast cancer cells.

ABSTRACTAberrant DNA methylation patterns have been reported in inflamed tissues and may play a role in disease. We studied DNA methylation and gene expression profiles of purified intestinal epithelial cells from ulcerative colitis patients, comparing inflamed and non-inflamed areas of the colon. We identified 577 differentially methylated sites (false discovery rate <0.2) mapping to 210 genes. From gene expression data from the same epithelial cells, we identified 62 differentially expressed genes with increased expression in the presence of inflammation at prostate cancer susceptibility genes PRAC1and PRAC2. Four genes showed inverse correlation between methylation and gene expression; ROR1, GXYLT2, FOXA2,and, notably, RARB, a gene previously identified as a tumor suppressor in colorectal adenocarcinoma as well as breast, lung and prostate cancer. We highlight targeted and specific patterns of DNA methylation and gene expression in epithelial cells from inflamed colon, while challenging the importance of epithelial cells in the pathogenesis of chronic inflammation.

The diagnostic criteria for antibody-mediated rejection (AMR) are continuously evolving. Here we investigated the clinical and molecular significance of different Banff microvascular inflammation (MVI) scores in transplant kidney biopsies. A total of 356 patients with clinically indicated kidney transplant biopsies were classified into three groups based on MVI scores of 0, 1, 2, or more for Groups 1–3, respectively. Gene expression profiles were assessed using arrays on a representative subset of 93 patients. The incidence of donor-specific anti-HLA antibodies was increased from 25% in Group 1 to 36% in Group 2 and to 54% in Group 3. Acute and chronic AMR were significantly more frequent in Group 3 (15% and 35%) compared with the Group 2 (3% and 15%) and Group 1 (0% and 5%), respectively. Gene expression profiles showed increased interferon-γ and rejection-induced, cytotoxic and regulatory T-cell, natural killer cell–associated and donor-specific antibody (DSA)–selective transcripts in Group 3 compared with Groups 1 and 2. There was no significant difference in gene expression profiles between the Groups 1 and 2. Increased intragraft expression of DSA–selective transcripts was found in the biopsies of C4d− Group 3 patients. Thus, an MVI score of 2 or more was significantly associated with a histological diagnosis of acute and chronic antibody-mediated rejection. Hence, increased intragraft DSA–selective gene transcripts may be used as molecular markers for AMR, especially in C4d− biopsies.

Intragraft gene expression profiles may help identify patients at risk of graft loss from transplant glomerulopathy, including endothelial cell, complement and interleukin associated transcripts. Supplemental digital content is available in the text.

Unrestrained receptor tyrosine kinase (RTK) signaling and epigenetic deregulation are root causes of tumorigenesis. We establish linkage between these processes by demonstrating that aberrant RTK signaling unleashed by oncogenic HRasG12Vor loss of negative feedback through Sproutygene deletion remodels histone modifications associated with active typical and super-enhancers. However, although both lesions disrupt the Ras-Erk axis, the expression programs, enhancer signatures, and transcription factor networks modulated upon HRasG12Vtransformation or Sproutydeletion are largely distinct. Oncogenic HRasG12Velevates histone 3 lysine 27 acetylation (H3K27ac) levels at enhancers near the transcription factor Gata4 and the kinase Prkcb, as well as their expression levels. We show that Gata4 is necessary for the aberrant gene expression and H3K27ac marking at enhancers, and Prkcb is required for the oncogenic effects of HRasG12V-driven cells. Taken together, our findings demonstrate that dynamic reprogramming of the cellular enhancer landscape is a major effect of oncogenic RTK signaling.

This study aimed to investigate global gene expression profiles of BK viremia and nephropathy (BKVN) samples using microarrays to investigate the immunologic response to BK virus.

We show that observations of pulsars with pulsed optical emission indicate that the peak flux scales according to the magnetic field strength at the light cylinder. The derived relationships indicate that the emission mechanism is common across all of the observed pulsars with periods ranging from 33 to 385 ms and ages of 1000-300,000 yr. It is noted that similar trends exist for ?-ray pulsars. Furthermore, the model proposed by Pacini and developed by Pacini and Salvati still has validity and gives an adequate explanation of the optical phenomena.

The pulsar PSR B0656+14 has been observed at g-ray, X-ray, EUV, and optical energies. These data are consistent with emission originating from a thermal stellar surface augmented by a hot, thermal "polar-cap" and an additional magnetospheric component. We have combined archival Extreme Ultraviolet Explorer (EUVE) and ROSAT data, together with recent analyses of optical photometry, to char acterize the surface thermal emission from PSR B0656+14. Because of differences in the EUVE and ROSAT flux for E < 0.18 keV, our combined-data models require a softer surface thermal component at closer distance with a larger intervening column, compared to models using only X-ray data. For a 0.1-2.0 keV source consisting of a dominant soft thermal blackbody that is augmented by both a smaller hot blackbody and a power-law optical component, we derive the source properties at 90% confidence to be Tsoft = (4.7-5.5) x 105 K, an absorbing column density of NH = (1.45-1.65) x 1020 cm-2, a distance of d/R10 = 135-190 pc, and Thot = (1.13-1.18) x 106 K.

The original version of this Article contained an error in the author affiliations. Vladislav V. Verkhusha was incorrectly associated with the School of Mathematics, Statistics & Applied Mathematics, National University of Ireland Galway, Galway, Ireland. The correct affiliation is Anatomy and Structural Biology, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA.

Motivation: One of the limiting factors in deciphering transcriptional regulatory networks is the effectiveness of motif-finding software. An emerging avenue for improving motif-finding accuracy aims to incorporate generalized binding constraints of related transcription factors (TFs), named familial binding profiles (FBPs), as priors in motif identification methods. A motif-finder can thus be ‘biased’ towards finding motifs from a particular TF family. However, current motif-finders allow only a single FBP to be used as a prior in a given motif-finding run. In addition, current FBP construction methods are based on manual clustering of position specific scoring matrices (PSSMs) according to the known structural properties of the TF proteins. Manual clustering assumes that the binding preferences of structurally similar TFs will also be similar. This assumption is not true, at least not for some TF families. Automatic PSSM clustering methods are thus required for augmenting the usefulness of FBPs. Results: A novel method is developed for automatic clustering of PSSM models. The resulting FBPs are incorporated into the SOMBRERO motif-finder, significantly improving its performance when finding motifs related to those that have been incorporated. SOMBRERO is thus the only existing de novo motif-finder that can incorporate knowledge of all known PSSMs in a given motif-finding run. Availability: The methods outlined will be incorporated into the next release of SOMBRERO, which is available from http://bioinf.nuigalway.ie/sombrero Contact: shaun.mahony@nuigalway.ie.

Motivation: The automatic identification of over-represented motifs present in a collection of sequences continues to be a challenging problem in computational biology. In this paper, we propose a self-organizing map of position weight matrices as an alternative method for motif discovery. The advantage of this approach is that it can be used to simultaneously characterize every feature present in the dataset, thus lessening the chance that weaker signals will be missed. Features identified are ranked in terms of over-representation relative to a background model. Results: We present an implementation of this approach, named SOMBRERO (self-organizing map for biological regulatory element recognition and ordering), which is capable of discovering multiple distinct motifs present in a single dataset. Demonstrated here are the advantages of our approach on various datasets and SOMBRERO's improved performance over two popular motif-finding programs, MEME and AlignACE. Availability: SOMBRERO is available free of charge from http://bioinf.nuigalway.ie/sombrero Contact: shaun.mahony@nuigalway.ie Supplementary information: http://bioinf.nuigalway.ie/sombrero/additional