BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the \u27strong hierarchical\u27 and \u27weak hierarchical\u27 models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the \u27independent\u27 model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies

Interactions among Carbon Dioxide, Heat, and Chemical Lures in Attracting the Bed Bug, Cimex lectularius L. (Hemiptera: Cimicidae)

Commercial bed bug (Cimex lectularius L.) monitors incorporating carbon dioxide (CO2), heat, and chemical lures are being used for detecting bed bugs; however, there are few reported studies on the effectiveness of chemical lures in bed bug monitors and the interactions among chemical lure, CO2, and heat. We screened 12 chemicals for their attraction to bed bugs and evaluated interactions among chemical lures, CO2, and heat. The chemical lure mixture consisting of nonanal, 1-octen-3-ol, spearmint oil, and coriander Egyptian oil was found to be most attractive to bed bugs and significantly increased the trap catches in laboratory bioassays. Adding this chemical lure mixture when CO2 was present increased the trap catches compared with traps baited with CO2 alone, whereas adding heat did not significantly increase trap catches when CO2 was present. Results suggest a combination of chemical lure and CO2 is essential for designing effective bed bug monitors

2-[(3S)-5-Oxooxolan-3-yl]isoindoline-1,3-dione

The oxolan-2-one ring in the title compound, C12H9NO4, has an envelope conformation with the atom linking the two five-membered rings being the flap atom

Knock Suppression of a Spark-Ignition Aviation Piston Engine Fuelled with Kerosene

Spark-ignition (SI) engine has a high power density, making it suitable for unmanned aerial vehicles. Normally, gasoline fuel with a high octane number (ON) is used for a spark-ignition engine. However, gasoline fuel is easy to be evaporated and has a low flash point which is unsafe for aviation engines. Kerosene with a high flash point is safer than gasoline. In this chapter, the combustion characteristics of kerosene for a spark-ignition aviation piston engine are analyzed. A three-dimensional (3D) model is setup, and the combustion process of the engine fuelled with kerosene is simulated. Later, the knock limit extension by water injection is evaluated experimentally. The results indicate that water injection can suppress the knock of SI engine with kerosene in some extent and the output power can be improved significantly

One-Step Nonaqueous Synthesis of Pure Phase TiO 2

Pure phase TiO2 nanomaterials were synthesized by an autoclaving treatment of TiCl4 with butanol as a single alcohol source. It was found that the control of molar ratio of TiCl4 to butanol played an important role in determining the TiO2 crystal phase and morphology. A high molar ratio of TiCl4 to butanol favored the formation of anatase nanoparticles, whereas rutile nanorods were selectively obtained at a low molar ratio of TiCl4 to butanol. Evaluation of the photocatalytic activity of the synthesized TiO2 was performed in terms of decomposition of organic dye rhodamine B under ultraviolet irradiation. It turned out that the as-synthesized TiO2 crystallites possessed higher photocatalytic activities toward bleaching rhodamine B than Degussa P25, benefiting from theirhigh surface area, small crystal size as well as high crystallinity

In vivo Characterization of a Selective, Orally Available, and Brain Penetrant Small Molecule GPR139 Agonist

Recently, our group along with another demonstrated that GPR139 can be activated by L-phenylalanine (L-Phe) and L-tryptophan (L-Trp) at physiologically relevant concentrations. GPR139 is discretely expressed in brain, with highest expression in medial habenula. Not only are the endogenous ligands catecholamine/serotonin precursors, but GPR139 expressing areas can directly/indirectly regulate the activity of catecholamine/serotonin neurons. Thus, GPR139 appears expressed in an interconnected circuit involved in mood, motivation, and anxiety. The aim of this study was to characterize a selective and brain penetrant GPR139 agonist (JNJ-63533054) in relevant in vivo models. JNJ-63533054 was tested for its effect on c-fos activation in the habenula and dorsal striatum. In vivo microdialysis experiments were performed in freely moving rats to measure basal levels of serotonin or dopamine (DA) in prefrontal cortex (mPFC) and nucleus accumbens (NAc). Finally, the compound was profiled in behavioral models of anxiety, despair, and anhedonia. The agonist (10–30 mg/kg, p.o.) did not alter c-fos expression in medial habenula or dorsal striatum nor neurotransmitter levels in mPFC or NAc. JNJ-63533054 (10 mg/kg p.o.) produced an anhedonic-like effect on urine sniffing, but had no significant effect in tail suspension, with no interaction with imipramine, no effect on naloxone place aversion, and no effect on learned helplessness. In the marble burying test, the agonist (10 mg/kg p.o.) produced a small anxiolytic-like effect, with no interaction with fluoxetine, and no effect in elevated plus maze (EPM). Despite GPR139 high expression in medial habenula, an area with connections to limbic and catecholaminergic/serotoninergic areas, the GPR139 agonist had no effect on c-fos in medial habenula. It did not alter catecholamine/serotonin levels and had a mostly silent signal in in vivo models commonly associated with these pathways. The physiological function of GPR139 remains elusive

GPR139 and Dopamine D2 Receptor Co-express in the Same Cells of the Brain and May Functionally Interact

GPR139, a Gq-coupled receptor that is activated by the essential amino acids L-tryptophan and L-phenylalanine, is predominantly expressed in the brain and pituitary. The physiological function of GPR139 remains elusive despite the availability of pharmacological tool agonist compounds and knock-out mice. Whole tissue RNA sequencing data from human, mouse and rat tissues revealed that GPR139 and the dopamine D2 receptor (DRD2) exhibited some similarities in their distribution patterns in the brain and pituitary gland. To determine if there was true co-expression of these two receptors, we applied double in situ hybridization in mouse tissues using the RNAscope® technique. GPR139 and DRD2 mRNA co-expressed in a majority of same cells within part of the dopaminergic mesolimbic pathways (ventral tegmental area and olfactory tubercle), the nigrostriatal pathway (compact part of substantia nigra and caudate putamen), and also the tuberoinfundibular pathway (arcuate hypothalamic nucleus and anterior lobe of pituitary). Both receptors mRNA also co-express in the same cells of the brain regions involved in responses to negative stimulus and stress, such as lateral habenula, lateral septum, interpeduncular nucleus, and medial raphe nuclei. GPR139 mRNA expression was detected in the dentate gyrus and the pyramidal cell layer of the hippocampus as well as the paraventricular hypothalamic nucleus. The functional interaction between GPR139 and DRD2 was studied in vitro using a calcium mobilization assay in cells co-transfected with both receptors from several species (human, rat, and mouse). The dopamine DRD2 agonist did not stimulate calcium response in cells expressing DRD2 alone consistent with the Gi signaling transduction pathway of this receptor. In cells co-transfected with DRD2 and GPR139 the DRD2 agonist was able to stimulate calcium response and its effect was blocked by either a DRD2 or a GPR139 antagonist supporting an in vitro interaction between GPR139 and DRD2. Taken together, these data showed that GPR139 and DRD2 are in position to functionally interact in native tissue

Changes in glycosylated proteins in colostrum and mature milk and their implication

IntroductionGlycosylation is one of the essential post-translational modifications that influences the function of milk proteins.MethodsIn the present study, 998 proteins and 764 glycosylated sites from 402 glycoproteins were identified in human milk by TMT labeling proteomics. Compared to human milk proteins, the glycoproteins were mainly enriched in cell adhesion, proteolysis, and defense/immune process.ResultsThe abundance of 353 glycosylated sites and their 179 parent proteins was quantified. After normalization to their parent protein’s abundance, 78 glycosylated sites in 56 glycoproteins and 10 glycosylated sites in 10 glycoproteins were significantly higher in colostrum and mature milk, respectively. These changed glycoproteins were mainly related to host defense. Intriguingly, one glycosylated site (Asp144) in IgA and two glycosylated sites (Asp38 and Asp1079) in tenascin are significantly upregulated even though their protein abundance was downregulated during lactation.DiscussionThis study helps us figure out the critical glycosylated sites in proteins that might influence their biological function in an unbiased way

Comparative Genomic Analysis of Latilactobacillus curvatus and L. sakei

In this study, the genomes of 19 Latilactobacillus curvatus and 40 L. sakei strains were comparatively analyzed. Average nucleic acid identity (ANI) and genome-wide colinearity indicated that the genomes of L. curvatus and L. sakei had weak nucleotide sequence homology, allowing them to be used as indicators to distinguish the two species. Pangenomes for these species were constructed, whose core gene functions were annotated. The results showed that the core genomes of L. curvatus and L. sakei were mainly involved in their basic metabolism. Analysis of individual genomes of the strains revealed that 1) both L. curvatus and L. sakei contained a wide range of genes encoding glycoside hydrolases, which are abundant genetic resources for catabolizing and metabolizing dietary fiber such as polysaccharides, lactose utilization, and lignocellulose; 2) antibiotic resistance genes were annotated in the genomes of three strains, which originate from horizontal gene transfer; 3) the unique arginine deiminase pathway of L. sakei, the serine dehydratase and guanine deaminase pathways of L. curvatus, and the glutamate decarboxylase pathway of several strains were identified, revealing that the acid tolerance mechanisms of these two species are different; and 4) genes encoding cold stress proteins were discovered, which endow the two species with good cold processing properties. Moreover, the genomes of some L. sakei strains contained gene clusters related to the biosynthesis of lactocin S and condensin. In conclusion, this study established taxonomic criteria for the two species and information on individual differences between their strains, which will provide a basis for the study of the physiological, biochemical, molecular genetic mechanisms of L. curvatus and L. sakei and their industrial applications