Functional genomics analysis of Phelan-McDermid syndrome 22q13 region during human neurodevelopment

Phelan-McDermid syndrome (PMS) is a neurodevelopmental disorder characterized by varying degrees of intellectual disability, severely delayed language development and specific facial features, and is caused by a deletion within chromosome 22q13.3. SHANK3, which is located at the terminal end of this region, has been repeatedly implicated in other neurodevelopmental disorders and deletion of this gene specifically is thought to cause much of the neurologic symptoms characteristic of PMS. However, it is still unclear to what extent SHANK3 deletions contribute to the PMS phenotype, and what other genes nearby are causal to the neurologic disease. In an effort to better understand the functional landscape of the PMS region during normal neurodevelopment, we assessed RNA-sequencing (RNA-seq) expression data collected from post-mortem brain tissue from developmentally normal subjects over the course of prenatal to adolescent age and analyzed expression changes of 65 genes on 22q13. We found that the majority of genes within this region were expressed in the brain, with ATNX10, MLC1, MAPK8IP2, and SULT4A1 having the highest overall expression. Analysis of the temporal profiles of the highest expressed genes revealed a trend towards peak expression during the early post-natal period, followed by a drop in expression later in development. Spatial analysis revealed significant region specific differences in the expression of SHANK3, MAPK8IP2, and SULT4A1. Region specific expression over time revealed a consistently unique gene expression profile within the cerebellum, providing evidence for a distinct developmental program within this region. Exon-specific expression of SHANK3 showed higher expression within exons contributing to known brain specific functional isoforms. Overall, we provide an updated roadmap of the PMS region, implicating several genes and time periods as important during neurodevelopment, with the hope that this information can help us better understand the phenotypic heterogeneity of PMS.

Predicting Cell Populations in Single Cell Mass Cytometry Data

Mass cytometry by time‐of‐flight (CyTOF) is a valuable technology for high‐dimensional analysis at the single cell level. Identification of different cell populations is an important task during the data analysis. Many clustering tools can perform this task, which is essential to identify “new” cell populations in explorative experiments. However, relying on clustering is laborious since it often involves manual annotation, which significantly limits the reproducibility of identifying cell‐populations across different samples. The latter is particularly important in studies comparing different conditions, for example in cohort studies. Learning cell populations from an annotated set of cells solves these problems. However, currently available methods for automatic cell population identification are either complex, dependent on prior biological knowledge about the populations during the learning process, or can only identify canonical cell populations. We propose to use a linear discriminant analysis (LDA) classifier to automatically identify cell populations in CyTOF data. LDA outperforms two state‐of‐the‐art algorithms on four benchmark datasets. Compared to more complex classifiers, LDA has substantial advantages with respect to the interpretable performance, reproducibility, and scalability to larger datasets with deeper annotations. We apply LDA to a dataset of ~3.5 million cells representing 57 cell populations in the Human Mucosal Immune System. LDA has high performance on abundant cell populations as well as the majority of rare cell populations, and provides accurate estimates of cell population frequencies. Further incorporating a rejection option, based on the estimated posterior probabilities, allows LDA to identify previously unknown (new) cell populations that were not encountered during training. Altogether, reproducible prediction of cell population compositions using LDA opens up possibilities to analyze large cohort studies based on CyTOF data. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Corticosteroid Action in the Brain: The Potential of Selective Receptor Modulation

Glucocorticoid hormones have important effects on brain function in the context of acute and chronic stress. Many of these are mediated by the glucocorticoid receptor (GR). GR has transcriptional activity which is highly context-specific and differs between tissues and even between cell types. The outcome of GR-mediated transcription depends on the interactome of associated coregulators. Selective GR modulators (SGRMs) are a class of GR ligands that can be used to activate only a subset of GR-coregulator interactions, thereby giving the possibility to induce a unique combination of agonistic and antagonistic GR properties. We describe SGRM action in animal models of brain function and pathology, and argue for their utility as molecular filters, to characterize context-specific GR interactome and transcriptional activity that are responsible for particular glucocorticoid-driven effects in cognitive processes such as memory consolidation. The ultimate objective of this approach is to identify molecular processes that are responsible for adaptive and maladaptive effects of glucocorticoids in the brain.

RNA sequencing data integration reveals an miRNA interactome of osteoarthritis cartilage

Objective

To uncover the microRNA (miRNA) interactome of the osteoarthritis (OA) pathophysiological process in the cartilage.

Methods

We performed RNA sequencing in 130 samples (n=35 and n=30 pairs for messenger RNA (mRNA) and miRNA, respectively) on macroscopically preserved and lesioned OA cartilage from the same patient and performed differential expression (DE) analysis of miRNA and mRNAs. To build an OA-specific miRNA interactome, a prioritisation scheme was applied based on inverse Pearson’s correlations and inverse DE of miRNAs and mRNAs. Subsequently, these were filtered by those present in predicted (TargetScan/microT-CDS) and/or experimentally validated (miRTarBase/TarBase) public databases. Pathway enrichment analysis was applied to elucidate OA-related pathways likely mediated by miRNA regulatory mechanisms.

Results

We found 142 miRNAs and 2387 mRNAs to be differentially expressed between lesioned and preserved OA articular cartilage. After applying prioritisation towards likely miRNA-mRNA targets, a regulatory network of 62 miRNAs targeting 238 mRNAs was created. Subsequent pathway enrichment analysis of these mRNAs (or genes) elucidated that genes within the ‘nervous system development’ are likely mediated by miRNA regulatory mechanisms (familywise error=8.4×10⁻⁵). Herein NTF3 encodes neurotrophin-3, which controls survival and differentiation of neurons and which is closely related to the nerve growth factor.

Conclusions

By an integrated approach of miRNA and mRNA sequencing data of OA cartilage, an OA miRNA interactome and related pathways were elucidated. Our functional data demonstrated interacting levels at which miRNA affects expression of genes in the cartilage and exemplified the complexity of functionally validating a network of genes that may be targeted by multiple miRNAs.

Natriuretic Peptides in Post-mortem Brain Tissue and Cerebrospinal Fluid of Non-demented Humans and Alzheimer's Disease Patients

Animal studies suggest the involvement of natriuretic peptides (NP) in several brain functions that are known to be disturbed during Alzheimer's disease (AD). However, it remains unclear whether such findings extend to humans. In this study, we aimed to: (1) map the gene expression and localization of NP and their receptors (NPR) in human post-mortem brain tissue; (2) compare the relative amounts of NP and NPR between the brain tissue of AD patients and non-demented controls, and (3) compare the relative amounts of NP between the cerebrospinal fluid (CSF) of AD patients and non-demented controls. Using the publicly available Allen Human Brain Atlas dataset, we mapped the gene expression of NP and NPR in healthy humans. Using immunohistochemistry, we visualized the localization of NP and NPR in the frontal cortex of AD patients (n = 10, mean age 85.8 ± 6.2 years) and non-demented controls (mean age = 80.2 ± 9.1 years). Using Western blotting and ELISA, we quantified the relative amounts of NP and NPR in the brain tissue and CSF of these AD patients and non-demented controls. Our results showed that NP and NPR genes were ubiquitously expressed throughout the brain in healthy humans. NP and NPR were present in various cellular structures including in neurons, astrocyte-like structures, and cerebral vessels in both AD patients and non-demented controls. Furthermore, we found higher amounts of NPR type-A in the brain of AD patients (p = 0.045) and lower amounts of NP type-B in the CSF of AD patients (p = 0.029). In conclusion, this study shows the abundance of NP and NPR in the brain of humans suggesting involvement of NP in various brain functions. In addition, our findings suggest alterations of NP levels in the brain of AD patients. The role of NP in the development and progression of AD remains to be elucidated.

A structural equation model for imaging genetics using spatial transcriptomics

Imaging genetics deals with relationships between genetic variation and imaging variables, often in a disease context. The complex relationships between brain volumes and genetic variants have been explored with both dimension reduction methods and model-based approaches. However, these models usually do not make use of the extensive knowledge of the spatio-anatomical patterns of gene activity. We present a method for integrating genetic markers (single nucleotide polymorphisms) and imaging features, which is based on a causal model and, at the same time, uses the power of dimension reduction. We use structural equation models to find latent variables that explain brain volume changes in a disease context, and which are in turn affected by genetic variants. We make use of publicly available spatial transcriptome data from the Allen Human Brain Atlas to specify the model structure, which reduces noise and improves interpretability. The model is tested in a simulation setting and applied on a case study of the Alzheimer’s Disease Neuroimaging Initiative.

Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells

Full-length RNA sequencing (RNA-Seq) has been applied to bulk tissue, cell lines and sorted cells to characterize transcriptomes, but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far. Although single splicing events have been described for ≤200 single cells with statistical confidence, full-length mRNA analyses for hundreds of cells have not been reported. Single-cell short-read 3' sequencing enables the identification of cellular subtypes, but full-length mRNA isoforms for these cell types cannot be profiled. We developed a method that starts with bulk tissue and identifies single-cell types and their full-length RNA isoforms without fluorescence-activated cell sorting. Using single-cell isoform RNA-Seq (ScISOr-Seq), we identified RNA isoforms in neurons, astrocytes, microglia, and cell subtypes such as Purkinje and Granule cells, and cell-type-specific combination patterns of distant splice sites. We used ScISOr-Seq to improve genome annotation in mouse Gencode version 10 by determining the cell-type-specific expression of 18,173 known and 16,872 novel isoforms.

How Metabolic State May Regulate Fear: Presence of Metabolic Receptors in the Fear Circuitry

Metabolic status impacts on the emotional brain to induce behavior that maintains energy balance. While hunger suppresses the fear circuitry to promote explorative food-seeking behavior, satiety or obesity may increase fear to prevent unnecessary risk-taking. Here we aimed to unravel which metabolic factors, that transfer information about the acute and the chronic metabolic status, are of primary importance to regulate fear, and to identify their sites of action within fear-related brain regions. We performed a de novo analysis of central and peripheral metabolic factors that can penetrate the blood–brain barrier using genome-wide expression data across the mouse brain from the Allen Brain Atlas (ABA). The central fear circuitry, as defined by subnuclei of the amygdala, the afferent hippocampus, the medial prefrontal cortex and the efferent periaqueductal gray, was enriched with metabolic receptors. Some of their corresponding ligands were known to modulate fear (e.g., estrogen and thyroid hormones) while others had not been associated with fear before (e.g., glucagon, ACTH). Additionally, several of these enriched metabolic receptors were coexpressed with well-described fear-modulating genes (Crh, Crhr1, or Crhr2). Co-expression analysis of monoamine markers and metabolic receptors suggested that monoaminergic nuclei have differential sensitivity to metabolic alterations. Serotonergic neurons expressed a large number of metabolic receptors (e.g., estrogen receptors, fatty acid receptors), suggesting a wide responsivity to metabolic changes. The noradrenergic system seemed to be specifically sensitive to hypocretin/orexin modulation. Taken together, we identified a number of novel metabolic factors (glucagon, ACTH) that have the potential to modulate the fear response. We additionally propose novel cerebral targets for metabolic factors (e.g., thyroid hormones) that modulate fear, but of which the sites of action are (largely) unknown.

IgG4-related disease mimicking pancreatic cancer: Case report and review of the literature

•

Pancreatic masses pose a diagnostic challenge, and cancer has to be always considered.

•

IgG4-related disease is a rare cause of pancreatic masses.

•

Biopsy from the pancreas is not always required if histopathology from a more accessible peripheral site lesion confirms the diagnosis.

•

Multiorgan involvement and aortitis should raise suspicion of IgG4-related disease.

Introduction

Most patients with pancreatic masses pose a diagnostic challenge when a benign lesion is suspected, and often, resection is needed before a benign diagnosis is confirmed.

Presentation of case

A 57 years old male patient presented with a pancreatic head mass, obstructive jaundice and submandibular lymph node enlargement. He also had a history of recurrent eye pain and redness, skin lesions, and benign prostatic hypertrophy. MRI showed a pancreatic head mass with double duct sign, aortic thickening, bilateral renal lesions, diffuse lymph node enlargement, and prostatic enlargement. FDG-PET/CT demonstrated abnormal uptake corresponding to the MRI lesions, and there were elevated IgG4 levels on blood investigations. Biopsy of an inguinal lymph node revealed infiltrates with IgG4 plasma cells, consistent with the diagnosis of IgG4 disease. The patient was treated with IV steroids and showed significant improvement.

Discussion

IgG4 related disease is a rare entity that is characterized by lesions that show heavy infiltration with IgG4 positive plasma cells, storiform fibrosis, and obliterative phlebitis. The pancreas is the most commonly involved organ, but several other organ systems are involved, and this helps in clinical suspicion of the diagnosis. A biopsy from any easily accessible site that shows the characteristic histological features is sufficient for diagnosis. Patients respond quickly to steroids, but recurrence is frequent.

Conclusion

IgG4 related disease is a rare cause of pancreatic tumorous lesions that need a high index of suspicion for diagnosis and should be differentiated from pancreatic neoplastic lesions.

Postoperative Cardiac Surgery Outcomes in a Statin-Native Population

Background

Statin utilization had been associated with improved survival after cardiac surgery. We aim to study whether perioperative treatment with statin could be associated with increased postoperative complications.

Design

This was a retrospective, descriptive, single-center study.

Settings

We analyzed morbidity after cardiac surgery as well as the outcome related to statin therapy in a tertiary cardiac center.

Patients

A total of 202 consecutive patients were enrolled over 1 year after cardiac surgery.

Intervention

Patients were divided into two groups; Group I - statin users and Group II - nonusers.

Measurements

Measurements were baseline and follow-up laboratory markers for muscular injury including cardiac muscle and hepatic injuries and renal injuries.

Results

The incidence of rhabdomyolysis and elevation of liver enzymes did not differ between both groups. Postoperative atrial fibrillation was significantly lower in the statin group (P = 0.02). In addition, peak cardiac troponin and creatine kinase-MB did not differ significantly in the statin group. Statin-treated group had significant lower length of mechanical ventilation, and length of stay in the Intensive Care Unit and hospital (P = 0.036, 0.04, and 0.027, respectively).

Conclusions

Therapy with statin before cardiac surgeries was not associated with high incidence of adverse events.

Co-expression Patterns between ATN1 and ATXN2 Coincide with Brain Regions Affected in Huntington's Disease

Cytosine-adenine-guanine (CAG) repeat expansions in the coding regions of nine polyglutamine (polyQ) genes (HTT, ATXN1, ATXN2, ATXN3, CACNA1A, ATXN7, ATN1, AR, and TBP) are the cause of several neurodegenerative diseases including Huntington’s disease (HD), six different spinocerebellar ataxias (SCAs), dentatorubral-pallidoluysian atrophy, and spinobulbar muscular atrophy. The expanded CAG repeat length in the causative gene is negatively related to the age-at-onset (AAO) of clinical symptoms. In addition to the expanded CAG repeat length in the causative gene, the normal CAG repeats in the other polyQ genes can affect the AAO, suggesting functional interactions between the polyQ genes. However, there is no detailed assessment of the relationships among polyQ genes in pathologically relevant brain regions. We used gene co-expression analysis to study the functional relationships among polyQ genes in different brain regions using the Allen Human Brain Atlas (AHBA), a spatial map of gene expression in the healthy brain. We constructed co-expression networks for seven anatomical brain structures, as well as a region showing a specific pattern of atrophy in HD patients detected by magnetic resonance imaging (MRI) of the brain. In this HD-associated region, we found that ATN1 and ATXN2 were co-expressed and shared co-expression partners which were enriched for DNA repair genes. We observed a similar co-expression pattern in the frontal lobe, parietal lobe, and striatum in which this relation was most pronounced. Given that the co-expression patterns for these anatomical structures were similar to those for the HD-associated region, our results suggest that their disruption is likely involved in HD pathology. Moreover, ATN1 and ATXN2 also shared many co-expressed genes with HTT, the causative gene of HD, across the brain. Although this triangular relationship among these three polyQ genes may also be dysregulated in other polyQ diseases, stronger co-expression patterns between ATN1 and ATXN2 observed in the HD-associated region, especially in the striatum, may be more specific to HD.

BrainScope: interactive visual exploration of the spatial and temporal human brain transcriptome

Spatial and temporal brain transcriptomics has recently emerged as an invaluable data source for molecular neuroscience. The complexity of such data poses considerable challenges for analysis and visualization. We present BrainScope: a web portal for fast, interactive visual exploration of the Allen Atlases of the adult and developing human brain transcriptome. Through a novel methodology to explore high-dimensional data (dual t-SNE), BrainScope enables the linked, all-in-one visualization of genes and samples across the whole brain and genome, and across developmental stages. We show that densities in t-SNE scatter plots of the spatial samples coincide with anatomical regions, and that densities in t-SNE scatter plots of the genes represent gene co-expression modules that are significantly enriched for biological functions. We also show that the topography of the gene t-SNE maps reflect brain region-specific gene functions, enabling hypothesis and data driven research. We demonstrate the discovery potential of BrainScope through three examples: (i) analysis of cell type specific gene sets, (ii) analysis of a set of stable gene co-expression modules across the adult human donors and (iii) analysis of the evolution of co-expression of oligodendrocyte specific genes over developmental stages. BrainScope is publicly accessible at www.brainscope.nl.

Cortical Spreading Depression Causes Unique Dysregulation of Inflammatory Pathways in a Transgenic Mouse Model of Migraine

Familial hemiplegic migraine type 1 (FHM1) is a rare monogenic subtype of migraine with aura caused by mutations in CACNA1A that encodes the α1A subunit of voltage-gated CaV2.1 calcium channels. Transgenic knock-in mice that carry the human FHM1 R192Q missense mutation ('FHM1 R192Q mice') exhibit an increased susceptibility to cortical spreading depression (CSD), the mechanism underlying migraine aura. Here, we analysed gene expression profiles from isolated cortical tissue of FHM1 R192Q mice 24 h after experimentally induced CSD in order to identify molecular pathways affected by CSD. Gene expression profiles were generated using deep serial analysis of gene expression sequencing. Our data reveal a signature of inflammatory signalling upon CSD in the cortex of both mutant and wild-type mice. However, only in the brains of FHM1 R192Q mice specific genes are up-regulated in response to CSD that are implicated in interferon-related inflammatory signalling. Our findings show that CSD modulates inflammatory processes in both wild-type and mutant brains, but that an additional unique inflammatory signature becomes expressed after CSD in a relevant mouse model of migraine.

NeuroD Factors Discriminate Mineralocorticoid From Glucocorticoid Receptor DNA Binding in the Male Rat Brain

In the limbic brain, mineralocorticoid receptors (MRs) and glucocorticoid receptors (GRs) both function as receptors for the naturally occurring glucocorticoids (corticosterone/cortisol) but mediate distinct effects on cellular physiology via transcriptional mechanisms. The transcriptional basis for specificity of these MR- vs GR-mediated effects is unknown. To address this conundrum, we have identified the extent of MR/GR DNA-binding selectivity in the rat hippocampus using chromatin immunoprecipitation followed by sequencing. We found 918 and 1450 nonoverlapping binding sites for MR and GR, respectively. Furthermore, 475 loci were co-occupied by MR and GR. De novo motif analysis resulted in a similar binding motif for both receptors at 100% of the target loci, which matched the known glucocorticoid response element (GRE). In addition, the Atoh/NeuroD consensus sequence was found in co-occurrence with all MR-specific binding sites but was absent for GR-specific or MR-GR overlapping sites. Basic helix-loop-helix family members Neurod1, Neurod2, and Neurod6 showed hippocampal expression and were hypothesized to bind the Atoh motif. Neurod2 was detected at rat hippocampal MR binding sites but not at GR-exclusive sites. All three NeuroD transcription factors acted as DNA-binding-dependent coactivators for both MR and GR in reporter assays in heterologous HEK293 cells, likely via indirect interactions with the receptors. In conclusion, a NeuroD family member binding to an additional motif near the GRE seems to drive specificity for MR over GR binding at hippocampal binding sites.

Brain transcriptome atlases: a computational perspective

The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases.

Statins in critical care: to give or not to give?

Owing to their immune modulatory, anti-inflammatory, antioxidant, antithrombotic, and endothelial action, statins are widely used in the critical care setting in several disease scenarios. The present review focuses on the evidence supporting an even wider utilization of statins in intensive care practice for diverse indications. A search of the literature was carried out in PubMed, Cochrane and EMBASE databases up to January 2016. Review articles, meta-analyses, and original trials on the effects of statin therapy in the intensive care unit (ICU) were included, by combining the following MeSH terms: "statins," "intensive care," "cardiac surgery," "sepsis," "acute respiratory distress syndrome," "pneumonia," "subarachnoid hemorrhage," "traumatic brain injury," and "critical illness." Case reports were excluded. No language restriction was applied. References were also searched for other potentially useful articles. It was concluded that beneficial effects of statins are observed in cardiac surgery; however, no robust evidence supports their effectiveness in diverse critical care settings. The decision to discontinue statins in native users should be taken in consideration of particular clinical circumstances.

Pancreatico-enteric fistula post pancreatic duct ligation for delayed haemorrhage complicating pancreaticoduodenectomy

•

Delayed post-pancreatectomy haemorrhage in association with pancreatic fistula is a grave complication.

•

Pancreatic duct occlusion may be considered in hemodynamically unstable patients.

•

Spontaneous development of a pancreatico-enteric fistula despite ligation of the pancreatic duct has never been reported to date.

Introduction

Pancreatic fistula remains the main cause for postoperative morbidity following pancreaticoduodenectomy. The coincidence of sentinel bleed prior to post pancreatectomy haemorrhage (PPH) and pancreatic fistula is associated with very high mortality.

Presentation of case

We report a case of pancreaticoduodenectomy complicated by postoperative leak and hematemesis. Severe delayed haemorrhage from the pancreatico-jejunostomy necessitated re-laparotomy and complete disconnection of the pancreatic anastomosis. Hemodynamic instability precluded a pancreatectomy or creation of a new anastomosis. A follow up MRI done 3 weeks after the patient’s discharge demonstrated a fistulous tract causing a communication between both the pancreatic and biliary systems and the enteric loop.

Discussion

Spontaneous development a pancreatico-enteric fistula despite ligation of the pancreatic duct and complete disconnection of the pancreatic anastomosis has never been reported in literature to date.

Conclusion

Pancreatic duct occlusion may be considered over a completion pancreatectomy or revisional pancreatic anastomosis in hemodynamically unstable and challenging cases.

Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology: a GWAS-based study using the Allen Human Brain Atlas

Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology.

Proton pump inhibitor co-prescription with dual antiplatelet therapy among patients with acute coronary syndrome in Qatar

BACKGROUND

There are increasing concerns about clinically significant interactions between proton pump inhibitors (PPIs) and clopidogrel, resulting in adverse cardiovascular outcomes in patients with acute coronary syndromes (ACS). However, published evidence on the prevalence and predictors of PPI use with dual antiplatelet therapy (DAPT) is scarce.

OBJECTIVE

This study investigated the prevalence of PPI use among patients with ACS receiving DAPT and possible predictors of co-prescribing the PPIs with the DAPT.

SETTING

Heart Hospital, a specialized tertiary care center in Qatar.

METHODOLOGY

A retrospective observational study of a prescription database was conducted. Subjects included 626 patients admitted between January and December 2012 with the diagnosis of ACS who received DAPT and discharged with or without a PPI. Univariate analysis and multivariate binary logistic regression analysis were performed to determine the predictors of PPI-DAPT co-prescription.

MAIN OUTCOME MEASURES

Prevalence of PPI co-prescribing with DAPT in proportions and percentages and odd ratios for the predictors of PPI-DAPT co-prescribing.

RESULTS

A total of 626 patients were analyzed for PPI prevalence, with 200 patients (32 %) being prescribed PPI with DAPT upon discharge. After controlling for confounders, PPI use on admission (aOR 14.5; 95 % CI 7.6-27.6, p < 0.001), nationality (aOR 3.2; 95 % CI 1.1-9.9, p = 0.041), and having a history of diabetes (aOR 0.5; 95 % CI 0.24-0.99, p = 0.046) significantly influenced PPI-DAPT co-prescribing. Users of PPI on admission compared to nonusers were about 15 times more likely to be prescribed PPI with DAPT upon discharge; likewise, having Qatari nationality increased the likelihood of co-prescribing PPI with DAPT upon discharge by three folds. Lastly, patients with a history of diabetes were 50 % less likely to be prescribed PPIs upon discharge compared to those with no history of diabetes.

CONCLUSION

The rate of PPI co-prescribing with DAPT in the population studied was relatively high. The strongest predictor of PPI co-prescription with DAPT upon discharge was PPI use on admission. Furthermore, PPI prescribing was significantly predicted by nationality and not having diabetes. Further studies are warranted to better predict the factors associated with PPI-DAPT co-prescription and to investigate rational prescribing of PPIs among ACS patients.

Shared Pathways Among Autism Candidate Genes Determined by Co-expression Network Analysis of the Developing Human Brain Transcriptome

Autism spectrum disorder (ASD) is a neurodevelopmental syndrome known to have a significant but complex genetic etiology. Hundreds of diverse genes have been implicated in ASD; yet understanding how many genes, each with disparate function, can all be linked to a single clinical phenotype remains unclear. We hypothesized that understanding functional relationships between autism candidate genes during normal human brain development may provide convergent mechanistic insight into the genetic heterogeneity of ASD. We analyzed the co-expression relationships of 455 genes previously implicated in autism using the BrainSpan human transcriptome database, across 16 anatomical brain regions spanning prenatal life through adulthood. We discovered modules of ASD candidate genes with biologically relevant temporal co-expression dynamics, which were enriched for functional ontologies related to synaptogenesis, apoptosis, and GABA-ergic neurons. Furthermore, we also constructed co-expression networks from the entire transcriptome and found that ASD candidate genes were enriched in modules related to mitochondrial function, protein translation, and ubiquitination. Hub genes central to these ASD-enriched modules were further identified, and their functions supported these ontological findings. Overall, our multi-dimensional co-expression analysis of ASD candidate genes in the normal developing human brain suggests the heterogeneous set of ASD candidates share transcriptional networks related to synapse formation and elimination, protein turnover, and mitochondrial function.

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale).

Regulatory elements can target genes over large genomic distances through long-range chromatin interactions. These interactions arise as a result of the three-dimensional (3D) conformation of chromosomes in the cell nucleus. This 3D conformation can also result in the co-localization of co-regulated genes. To investigate this, we asked whether genome-wide chromatin interactions can predict co-expression patterns of genes. To address this question, we characterized 3D interactions between genes, captured by Hi-C measurements, by a network, termed chromatin interaction network (CIN). We applied scale-aware topological measures to the network to comprehensively characterize the chromatin interactions at different scales, ranging from direct interaction between gene pairs to chromatin compartment interactions. We then used multi-scale chromatin interactions to predict spatial co-expression patterns in the mouse cortex. The results show that the prediction performance improves when scale-aware topological measures of the multi-resolution chromatin interaction network are used.