We show here that combining two existing genome wide association studies (GWAS) yields additional biologically relevant information, beyond that obtained by either GWAS separately. We propose Joint ...GWAS Analysis, a method that compares a pair of GWAS for similarity among the top SNP associations, top genes identified, gene functional clusters, and top biological pathways. We show that Joint GWAS Analysis identifies additional enriched biological pathways that would be missed by traditional Single-GWAS analysis. Furthermore, we examine the similarities of six complex genetic disorders at the SNP-level, gene-level, gene-cluster-level, and pathway-level. We make concrete hypotheses regarding novel pathway associations for several complex disorders considered, based on the results of Joint GWAS Analysis. Together, these results demonstrate that common complex disorders share substantially more genomic architecture than has been previously realized and that the meta-analysis of GWAS needs not be limited to GWAS of the same phenotype to be informative.
Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with ...mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.
Bridging (Thionylimido)metal Complexes McGeachie, Liam J. R; Bühl, Michael; Cordes, David B ...
Inorganic chemistry,
06/2021, Letnik:
60, Številka:
12
Journal Article
Recenzirano
Odprti dostop
We report the first examples of the thionylimido ligand acting as a μ2-bridging ligand between two transition-metal centers; using Cp2Ti(NSO)2, we describe bi- and tetrametallic systems.
Introduction
While whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related ...phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma‐related phenotypes.
Methods
We applied several WGP methods to a well‐phenotyped cohort of 832 children with mild‐to‐moderate asthma from CAMP. We assessed narrow‐sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre‐ and post‐bronchodilator forced expiratory volume in 1 sec (FEV1), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort.
Results
We found that longitudinal lung function phenotypes demonstrated significant narrow‐sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve AUCs 56% to 62%). Including additional demographic covariates in the models increased prediction 4–8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts.
Conclusions
Longitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP‐prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma‐related heritable traits.
Whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. We show that WGP methods can significantly predict longitudinal lung function patterns, which have high heritability.
The application of large-scale metabolomic profiling provides new opportunities for realizing the potential of omics-based precision medicine for asthma. By leveraging data from over 14,000 ...individuals in four distinct cohorts, this study identifies and independently replicates 17 steroid metabolites whose levels were significantly reduced in individuals with prevalent asthma. Although steroid levels were reduced among all asthma cases regardless of medication use, the largest reductions were associated with inhaled corticosteroid (ICS) treatment, as confirmed in a 4-year low-dose ICS clinical trial. Effects of ICS treatment on steroid levels were dose dependent; however, significant reductions also occurred with low-dose ICS treatment. Using information from electronic medical records, we found that cortisol levels were substantially reduced throughout the entire 24-hour daily period in patients with asthma who were treated with ICS compared to those who were untreated and to patients without asthma. Moreover, patients with asthma who were treated with ICS showed significant increases in fatigue and anemia as compared to those without ICS treatment. Adrenal suppression in patients with asthma treated with ICS might, therefore, represent a larger public health problem than previously recognized. Regular cortisol monitoring of patients with asthma treated with ICS is needed to provide the optimal balance between minimizing adverse effects of adrenal suppression while capitalizing on the established benefits of ICS treatment.
Dynamin is essential for clathrin‐mediated endocytosis (CME). We describe the Dyngo™ series of dynamin inhibitors with greatly improved potency, reduced cytotoxicity and reduced detergent binding ...compared to their parent, dynasore. Dyngo compound 4a is 37‐fold more potent for dynamin inhibition and at least sixfold more potent for CME inhibition in cells and nerve terminals. This series are the first to target one conformational state of dynamin, inhibiting lipid‐associated helical dynamin but not dynamin rings induced by self‐assembly or SH3‐domain‐containing proteins.
Dynamin GTPase activity increases when it oligomerizes either into helices in the presence of lipid templates or into rings in the presence of SH3 domain proteins. Dynasore is a dynamin inhibitor of moderate potency (IC50 ˜ 15 μM in vitro). We show that dynasore binds stoichiometrically to detergents used for in vitro drug screening, drastically reducing its potency (IC50 = 479 μM) and research tool utility. We synthesized a focused set of dihydroxyl and trihydroxyl dynasore analogs called the Dyngo™ compounds, five of which had improved potency, reduced detergent binding and reduced cytotoxicity, conferred by changes in the position and/or number of hydroxyl substituents. The Dyngo compound 4a was the most potent compound, exhibiting a 37‐fold improvement in potency over dynasore for liposome‐stimulated helical dynamin activity. In contrast, while dynasore about equally inhibited dynamin assembled in its helical or ring states, 4a and 6a exhibited >36‐fold reduced activity against rings, suggesting that they can discriminate between helical or ring oligomerization states. 4a and 6a inhibited dynamin‐dependent endocytosis of transferrin in multiple cell types (IC50 of 5.7 and 5.8 μM, respectively), at least sixfold more potently than dynasore, but had no effect on dynamin‐independent endocytosis of cholera toxin. 4a also reduced synaptic vesicle endocytosis and activity‐dependent bulk endocytosis in cultured neurons and synaptosomes. Overall, 4a and 6a are improved and versatile helical dynamin and endocytosis inhibitors in terms of potency, non‐specific binding and cytotoxicity. The data further suggest that the ring oligomerization state of dynamin is not required for clathrin‐mediated endocytosis.
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