Structural variation and fusion detection using targeted sequencing data from circulating cell free DNA

MOTIVATION: Cancer is a complex disease that involves rapidly evolving cells, often forming multiple distinct clones. In order to effectively understand progression of a patient-specific tumor, one needs to comprehensively sample tumor DNA at multiple time points, ideally obtained through inexpensive and minimally invasive techniques. Current sequencing technologies make the 'liquid biopsy' possible, which involves sampling a patient's blood or urine and sequencing the circulating cell free DNA (cfDNA). A certain percentage of this DNA originates from the tumor, known as circulating tumor DNA (ctDNA). The ratio of ctDNA may be extremely low in the sample, and the ctDNA may originate from multiple tumors or clones. These factors present unique challenges for applying existing tools and workflows to the analysis of ctDNA, especially in the detection of structural variations which rely on sufficient read coverage to be detectable. RESULTS: Here we introduce SViCT , a structural variation (SV) detection tool designed to handle the challenges associated with cfDNA analysis. SViCT can detect breakpoints and sequences of various structural variations including deletions, insertions, inversions, duplications and translocations. SViCT extracts discordant read pairs, one-end anchors and soft-clipped/split reads, assembles them into contigs, and re-maps contig intervals to a reference genome using an efficient k-mer indexing approach. The intervals are then joined using a combination of graph and greedy algorithms to identify specific structural variant signatures. We assessed the performance of SViCT and compared it to state-of-the-art tools using simulated cfDNA datasets with properties matching those of real cfDNA samples. The positive predictive value and sensitivity of our tool was superior to all the tested tools and reasonable performance was maintained down to the lowest dilution of 0.01% tumor DNA in simulated datasets. Additionally, SViCT was able to detect all known SVs in two real cfDNA reference datasets (at 0.6-5% ctDNA) and predict a novel structural variant in a prostate cancer cohort

Altered Neurocircuitry in the Dopamine Transporter Knockout Mouse Brain

The plasma membrane transporters for the monoamine neurotransmitters dopamine, serotonin, and norepinephrine modulate the dynamics of these monoamine neurotransmitters. Thus, activity of these transporters has significant consequences for monoamine activity throughout the brain and for a number of neurological and psychiatric disorders. Gene knockout (KO) mice that reduce or eliminate expression of each of these monoamine transporters have provided a wealth of new information about the function of these proteins at molecular, physiological and behavioral levels. In the present work we use the unique properties of magnetic resonance imaging (MRI) to probe the effects of altered dopaminergic dynamics on meso-scale neuronal circuitry and overall brain morphology, since changes at these levels of organization might help to account for some of the extensive pharmacological and behavioral differences observed in dopamine transporter (DAT) KO mice. Despite the smaller size of these animals, voxel-wise statistical comparison of high resolution structural MR images indicated little morphological change as a consequence of DAT KO. Likewise, proton magnetic resonance spectra recorded in the striatum indicated no significant changes in detectable metabolite concentrations between DAT KO and wild-type (WT) mice. In contrast, alterations in the circuitry from the prefrontal cortex to the mesocortical limbic system, an important brain component intimately tied to function of mesolimbic/mesocortical dopamine reward pathways, were revealed by manganese-enhanced MRI (MEMRI). Analysis of co-registered MEMRI images taken over the 26 hours after introduction of Mn^(2+) into the prefrontal cortex indicated that DAT KO mice have a truncated Mn^(2+) distribution within this circuitry with little accumulation beyond the thalamus or contralateral to the injection site. By contrast, WT littermates exhibit Mn^(2+) transport into more posterior midbrain nuclei and contralateral mesolimbic structures at 26 hr post-injection. Thus, DAT KO mice appear, at this level of anatomic resolution, to have preserved cortico-striatal-thalamic connectivity but diminished robustness of reward-modulating circuitry distal to the thalamus. This is in contradistinction to the state of this circuitry in serotonin transporter KO mice where we observed more robust connectivity in more posterior brain regions using methods identical to those employed here

Perisylvian white matter connectivity in the human right hemisphere

Background By using diffusion tensor magnetic resonance imaging (DTI) and subsequent tractography, a perisylvian language network in the human left hemisphere recently has been identified connecting Brocas's and Wernicke's areas directly (arcuate fasciculus) and indirectly by a pathway through the inferior parietal cortex. Results Applying DTI tractography in the present study, we found a similar three-way pathway in the right hemisphere of 12 healthy individuals: a direct connection between the superior temporal and lateral frontal cortex running in parallel with an indirect connection. The latter composed of a posterior segment connecting the superior temporal with the inferior parietal cortex and an anterior segment running from the inferior parietal to the lateral frontal cortex. Conclusion The present DTI findings suggest that the perisylvian inferior parietal, superior temporal, and lateral frontal corticies are tightly connected not only in the human left but also in the human right hemisphere

Risk Factors for Intra-Abdominal Candidiasis in Intensive Care Units: Results from EUCANDICU Study

Introduction: Intra-abdominal infections represent the second most frequently acquired infection in the intensive care unit (ICU), with mortality rates ranging from 20% to 50%. Candida spp. may be responsible for up to 10–30% of cases. This study assesses risk factors for development of intra-abdominal candidiasis (IAC) among patients admitted to ICU. Methods: We performed a case–control study in 26 European ICUs during the period January 2015–December 2016. Patients at least 18 years old who developed an episode of microbiologically documented IAC during their stay in the ICU (at least 48 h after admission) served as the case cohort. The control group consisted of adult patients who did not develop episodes of IAC during ICU admission. Matching was performed at a ratio of 1:1 according to time at risk (i.e. controls had to have at least the same length of ICU stay as their matched cases prior to IAC onset), ICU ward and period of study. Results: During the study period, 101 case patients with a diagnosis of IAC were included in the study. On univariate analysis, severe hepatic failure, prior receipt of antibiotics, prior receipt of parenteral nutrition, abdominal drain, prior bacterial infection, anastomotic leakage, recurrent gastrointestinal perforation, prior receipt of antifungal drugs and higher median number of abdominal surgical interventions were associated with IAC development. On multivariate analysis, recurrent gastrointestinal perforation (OR 13.90; 95% CI 2.65–72.82, p = 0.002), anastomotic leakage (OR 6.61; 95% CI 1.98–21.99, p = 0.002), abdominal drain (OR 6.58; 95% CI 1.73–25.06, p = 0.006), prior receipt of antifungal drugs (OR 4.26; 95% CI 1.04–17.46, p = 0.04) or antibiotics (OR 3.78; 95% CI 1.32–10.52, p = 0.01) were independently associated with IAC. Conclusions: Gastrointestinal perforation, anastomotic leakage, abdominal drain and prior receipt of antifungals or antibiotics may help to identify critically ill patients with higher probability of developing IAC. Prospective studies are needed to identify which patients will benefit from early antifungal treatment

Alterations of renal phenotype and gene expression profiles due to protein overload in NOD-related mouse strains

BACKGROUND: Despite multiple causes, Chronic Kidney Disease is commonly associated with proteinuria. A previous study on Non Obese Diabetic mice (NOD), which spontaneously develop type 1 diabetes, described histological and gene expression changes incurred by diabetes in the kidney. Because proteinuria is coincident to diabetes, the effects of proteinuria are difficult to distinguish from those of other factors such as hyperglycemia. Proteinuria can nevertheless be induced in mice by peritoneal injection of Bovine Serum Albumin (BSA). To gain more information on the specific effects of proteinuria, this study addresses renal changes in diabetes resistant NOD-related mouse strains (NON and NOD.B10) that were made to develop proteinuria by BSA overload. METHODS: Proteinuria was induced by protein overload on NON and NOD.B10 mouse strains and histology and microarray technology were used to follow the kidney response. The effects of proteinuria were assessed and subsequently compared to changes that were observed in a prior study on NOD diabetic nephropathy. RESULTS: Overload treatment significantly modified the renal phenotype and out of 5760 clones screened, 21 and 7 kidney transcripts were respectively altered in the NON and NOD.B10. Upregulated transcripts encoded signal transduction genes, as well as markers for inflammation (Calmodulin kinase beta). Down-regulated transcripts included FKBP52 which was also down-regulated in diabetic NOD kidney. Comparison of transcripts altered by proteinuria to those altered by diabetes identified mannosidase 2 alpha 1 as being more specifically induced by proteinuria. CONCLUSION: By simulating a component of diabetes, and looking at the global response on mice resistant to the disease, by virtue of a small genetic difference, we were able to identify key factors in disease progression. This suggests the power of this approach in unraveling multifactorial disease processes

Identification and Classification of Hubs in Brain Networks

Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles

Differential Development of Human Brain White Matter Tracts

Neuroscience is increasingly focusing on developmental factors related to human structural and functional connectivity. Unfortunately, to date, diffusion-based imaging approaches have only contributed modestly to these broad objectives, despite the promise of diffusion-based tractography. Here, we report a novel data-driven approach to detect similarities and differences among white matter tracts with respect to their developmental trajectories, using 64-direction diffusion tensor imaging. Specifically, using a cross-sectional sample comprising 144 healthy individuals (7 to 48 years old), we applied k-means cluster analysis to separate white matter voxels based on their age-related trajectories of fractional anisotropy. Optimal solutions included 5-, 9- and 14-clusters. Our results recapitulate well-established tracts (e.g., internal and external capsule, optic radiations, corpus callosum, cingulum bundle, cerebral peduncles) and subdivisions within tracts (e.g., corpus callosum, internal capsule). For all but one tract identified, age-related trajectories were curvilinear (i.e., inverted ‘U-shape’), with age-related increases during childhood and adolescence followed by decreases in middle adulthood. Identification of peaks in the trajectories suggests that age-related losses in fractional anisotropy occur as early as 23 years of age, with mean onset at 30 years of age. Our findings demonstrate that data-driven analytic techniques may be fruitfully applied to extant diffusion tensor imaging datasets in normative and neuropsychiatric samples

Study of Z boson production in pPb collisions at √sNN=5.02 TeV

The production of Z bosons in pPb collisions at root S-NN = 5.02 TeV is studied by the CMS experiment via the electron and muon decay channels. The inclusive cross section is compared to pp collision predictions, and found to scale with the number of elementary nucleon-nucleon collisions. The differential cross sections as a function of the Z boson rapidity and transverse momentum are measured. Though they are found to be consistent within uncertainty with theoretical predictions both with and without nuclear effects, the forward-backward asymmetry suggests the presence of nuclear effects at large rapidities. These results provide new data for constraining nuclear parton distribution functions