Robust and Efficient Modeling for Gene-Environment and Gene-Gene Interactions in Longitudinal Cohort Studies.

While there have been extensive statistical methods on gene-environment interaction (GEI) in case-control studies, little attention has been given to robust and efficient modeling of GEI in longitudinal cohort studies. In a two-way table for GEI with row and column as categorical variables, a conventional saturated model involves estimation of distinct interaction effect for each cell. However, the degrees of freedom (df) for testing interaction can grow quickly with increasing number of categories, resulting in decreased efficiency and reduced power for detecting interaction. This dissertation considers the problem of modeling GEI with repeated measures data on a quantitative trait using parsimonious models for non-additivity proposed in the classical Analysis of Variance literature. We first provide an overview of these classical models and explore the interaction structures by simply reducing repeated measurements to summary level cell means. In the first project, we modify the cell-mean method and propose a parametric bootstrap approach using these interaction models. Both methods account for the unbalanced and longitudinal nature of the data. In the second project, we propose a shrinkage estimator that combines estimates from a saturated interaction model and Tukey's single df model for non-additivity. It is useful for conducting multiple GEI tests where distinct interaction patterns could occur in different genetic markers. The proposed estimator is robust to various interaction structures and the corresponding test is valid based on simulation results. In the third project, we focus on additive main effects and multiplicative interaction (AMMI) models. We develop an alternating maximum likelihood estimation procedure for AMMI models and approximate the null distribution of the likelihood ratio test statistic by a chi-square with fractional df. The proposed methods are illustrated using data from the Normative Aging Study and the Multi-Ethnic Study of Atherosclerosis. Both datasets come from longitudinal cohort studies involving rich genetic data and several environmental exposure factors that could be time varying or time invariant. Overall, this dissertation contributes to adaptation of classical interaction models to longitudinal studies, with the goal of understanding the dynamic interplay between genes and environment over time.PhDBiostatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108871/1/yianko_1.pd

Novel Likelihood Ratio Tests for Screening Gene‐Gene and Gene‐Environment Interactions With Unbalanced Repeated‐Measures Data

There has been extensive literature on modeling gene‐gene interaction (GGI) and gene‐environment interaction (GEI) in case‐control studies with limited literature on statistical methods for GGI and GEI in longitudinal cohort studies. We borrow ideas from the classical two‐way analysis of variance literature to address the issue of robust modeling of interactions in repeated‐measures studies. While classical interaction models proposed by Tukey and Mandel have interaction structures as a function of main effects, a newer class of models, additive main effects and multiplicative interaction (AMMI) models, do not have similar restrictive assumptions on the interaction structure. AMMI entails a singular value decomposition of the cell residual matrix after fitting the additive main effects and has been shown to perform well across various interaction structures. We consider these models for testing GGI and GEI from two perspectives: likelihood ratio test based on cell means and a regression‐based approach using individual observations. Simulation results indicate that both approaches for AMMI models lead to valid tests in terms of maintaining the type I error rate, with the regression approach having better power properties. The performance of these models was evaluated across different interaction structures and 12 common epistasis patterns. In summary, AMMI model is robust with respect to misspecified interaction structure and is a useful screening tool for interaction even in the absence of main effects. We use the proposed methods to examine the interplay between the hemochromatosis gene and cumulative lead exposure on pulse pressure in the Normative Aging Study.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/99643/1/gepi21744-sup-0001-si.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99643/2/gepi21744.pd

Deletion of miR-150 Exacerbates Retinal Vascular Overgrowth in High-Fat-Diet Induced Diabetic Mice

Diabetic retinopathy (DR) is the leading cause of blindness among American adults above 40 years old. The vascular complication in DR is a major cause of visual impairment, making finding therapeutic targets to block pathological angiogenesis a primary goal for developing DR treatments. MicroRNAs (miRs) have been proposed as diagnostic biomarkers and potential therapeutic targets for various ocular diseases including DR. In diabetic animals, the expression levels of several miRs, including miR-150, are altered. The expression of miR-150 is significantly suppressed in pathological neovascularization in mice with hyperoxia-induced retinopathy. The purpose of this study was to investigate the functional role of miR-150 in the development of retinal microvasculature complications in high-fat-diet (HFD) induced type 2 diabetic mice. Wild type (WT) and miR-150 null mutant (miR-150-/-) male mice were given a HFD (59% fat calories) or normal chow diet. Chronic HFD caused a decrease of serum miR-150 in WT mice. Mice on HFD for 7 months (both WT and miR-150-/-) had significant decreases in retinal light responses measured by electroretinograms (ERGs). The retinal neovascularization in miR-150-/--HFD mice was significantly higher compared to their age matched WT-HFD mice, which indicates that miR-150 null mutation exacerbates chronic HFD-induced neovascularization in the retina. Overexpression of miR-150 in cultured endothelial cells caused a significant reduction of vascular endothelial growth factor receptor 2 (VEGFR2) protein levels. Hence, deletion of miR-150 significantly increased the retinal pathological angiogenesis in HFD induced type 2 diabetic mice, which was in part through VEGFR2

Testing departure from additivity in Tukey's model using shrinkage: application to a longitudinal setting

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109558/1/sim6281-sup-0001-WebBased.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/109558/2/sim6281.pd

A Novel Biomarker of Oxidative Stress is Associated with Risk of Death in Patients with Coronary Artery Disease

Background—Free radical scavengers have failed to improve patient outcomes promoting the concept that clinically important oxidative stress (OS) may be mediated by alternative mechanisms. We sought to examine the association of emerging aminothiol markers of non-free radical mediated oxidative stress with clinical outcomes. Methods and Results—Plasma levels of reduced (cysteine and glutathione) and oxidized (cystine and glutathione disulphide) aminothiols were quantified by high performance liquid chromatography in 1411 patients undergoing coronary angiography (mean age 63 years, male 66%). All patients were followed for a mean of 4.7±2.1 years for the primary outcome of all-cause death (n=247). Levels of cystine (oxidized) and glutathione (reduced) were associated with risk of death (p\u3c0.001 both) before and after adjustment for covariates. High cystine and low glutathione levels (\u3e+1 SD & \u3c-1 SD respectively) were associated with higher mortality (adjusted HR 1.63 (95% CI 1.19-2.21; HR 2.19 (95% CI 1.50-3.19), respectively) compared to those outside these thresholds. Furthermore, the ratio of cystine/glutathione was also significantly associated with mortality (adjusted HR 1.92 (95% CI 1.39-2.64) and was independent of and additive to hs-CRP level. Similar associations were found for other outcomes of cardiovascular death and combined death and myocardial infarction. Conclusions—A high burden of OS, quantified by the plasma aminothiols, cystine, glutathione and their ratio is associated with mortality in patients with CAD, a finding that is independent of and additive to the inflammatory burden. Importantly, this data supports the emerging role of non-free radical biology in driving clinically important oxidative stress

Dexmedetomidine Ameliorates Sleep Deprivation-Induced Depressive Behaviors in Mice

Purpose Sleep deprivation induces depressive symptoms. Dexmedetomidine is a α2-adrenoreceptor agonist and this drug possesses sedative, anxiolytic, analgesic, and anesthetic-sparing effect. In this study, the action of dexmedetomidine on sleep deprivation-induced depressive behaviors was investigated using mice. Methods For the inducing of sleep deprivation, the mice were placed inside a water cage containing 15 platforms and filled with water up to 1 cm below the platform surface for 7 days. One day after sleep deprivation, dexmedetomidine at the respective dosage (0.5, 1, and 2 μg/kg) was intraperitoneally treated into the mice, one time per a day during 6 days. Then, forced swimming test and tail suspension test were conducted. Immunohistochemistry for tyrosine hydroxylase (TH), 5-hydroxytryptamine (5-HT; serotonin), tryptophan hydroxylase (TPH) and western blot for D1 dopamine receptor were also performed. Results Sleep deprivation increased the immobility latency in the forced swimming test and tail suspension test. The expressions of TPH, 5-HT, and D1 dopamine receptor were decreased, whereas, TH expression was increased by sleep deprivation. Dexmedetomidine decreased the immobility latency and increased the expressions of TPH, 5-HT, and D1 dopamine receptor, whereas, HT expression was decreased by dexmedetomidine treatment. Conclusions In our results, dexmedetomidine alleviated sleep deprivation-induced depressive behaviors by increasing 5-HT synthesis and by decreasing dopamine production with up-regulation of D1 dopamine receptor

A High Sensitivity Three-Dimensional-Shape Sensing Patch Prepared by Lithography and Inkjet Printing

A process combining conventional photolithography and a novel inkjet printing method for the manufacture of high sensitivity three-dimensional-shape (3DS) sensing patches was proposed and demonstrated. The supporting curvature ranges from 1.41 to 6.24 × 10−2 mm−1 and the sensing patch has a thickness of less than 130 μm and 20 × 20 mm2 dimensions. A complete finite element method (FEM) model with simulation results was calculated and performed based on the buckling of columns and the deflection equation. The results show high compatibility of the drop-on-demand (DOD) inkjet printing with photolithography and the interferometer design also supports bi-directional detection of deformation. The 3DS sensing patch can be operated remotely without any power consumption. It provides a novel and alternative option compared with other optical curvature sensors

Genome-wide analysis of DNA methylation patterns in horse

Background: DNA methylation is an epigenetic regulatory mechanism that plays an essential role in mediating biological processes and determining phenotypic plasticity in organisms. Although the horse reference genome and whole transcriptome data are publically available the global DNA methylation data are yet to be known. Results: We report the first genome-wide DNA methylation characteristics data from skeletal muscle, heart, lung, and cerebrum tissues of thoroughbred (TH) and Jeju (JH) horses, an indigenous Korea breed, respectively by methyl-DNA immunoprecipitation sequencing. The analysis of the DNA methylation patterns indicated that the average methylation density was the lowest in the promoter region, while the density in the coding DNA sequence region was the highest. Among repeat elements, a relatively high density of methylation was observed in long interspersed nuclear elements compared to short interspersed nuclear elements or long terminal repeat elements. We also successfully identified differential methylated regions through a comparative analysis of corresponding tissues from TH and JH, indicating that the gene body regions showed a high methylation density. Conclusions: We provide report the first DNA methylation landscape and differentially methylated genomic regions (DMRs) of thoroughbred and Jeju horses, providing comprehensive DMRs maps of the DNA methylome. These data are invaluable resource to better understanding of epigenetics in the horse providing information for the further biological function analyses.open1