Biostatistics Commons^™

Genetic Predictors Of Metabolic Side Effects Of Diuretic Therapy, Jorge L. Del Aguila

Dissertations and Theses (Open Access)

Thiazide diuretics are a recommended first-line monotherapy for hypertension (i.e.SBP>140 mmHg or DBP>90 mmHg). Even so, diuretics are associated with adverse metabolic side effects, such as hyperlipidemia, hyperglycemia and hypokalemia which increase the risk of developing type II diabetes. This thesis used three analytical strategies to identify and quantify genetic factors that contribute to the development of adverse metabolic effects due to thiazide diuretic treatment. I performed a genome-wide association study (GWAS) and meta-analysis of the change in fasting plasma glucose and triglycerides in response to HCTZ from two different clinical trials: the Pharmacogenomic Evaluation of Antihypertensive Responses …

A Study Of Joinpoint Models For Longitudinal Data, Libo Zhou

UNLV Theses, Dissertations, Professional Papers, and Capstones

In many medical studies, data are collected simultaneously on multiple biomarkers from each individual. Levels of these biomarkers are measured periodically over certain time duration, giving rise to longitudinal trajectories. The subjects under study may also be subject to dropout due to several competing causes, the likelihood of which may be affected by the levels of these biomarkers. In this dissertation, we investigate flexible Bayesian modeling of such data, taking into account any available covariate information as well as possible censoring of the drop-out times. We propose joint models for multiple biomarkers with multiple causes of dropout. Our proposed models …

Penalized Regressions For Variable Selection Model, Single Index Model And An Analysis Of Mass Spectrometry Data., Yubing Wan

Electronic Theses and Dissertations

The focus of this dissertation is to develop statistical methods, under the framework of penalized regressions, to handle three different problems. The first research topic is to address missing data problem for variable selection models including elastic net (ENet) method and sparse partial least squares (SPLS). I proposed a multiple imputation (MI) based weighted ENet (MI-WENet) method based on the stacked MI data and a weighting scheme for each observation. Numerical simulations were implemented to examine the performance of the MIWENet method, and compare it with competing alternatives. I then applied the MI-WENet method to examine the predictors for the …

A General Approach To Detect Gene (G)-Environment (E) Additive Interaction Leveraging G-E Independence In Case-Control Studies, Eric Tchetgen Tchetgen, Tamar Sofer, Benedict H.W. Wong

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Novel Targeted Learning Method For Quantitative Trait Loci Mapping, Hui Wang, Zhongyang Zhang, Sherri Rose, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We present a novel semiparametric method for quantitative trait loci (QTL) mapping in experimental crosses. Conventional genetic mapping methods typically assume parametric models with Gaussian errors and obtain parameter estimates through maximum likelihood estimation. In contrast with univariate regression and interval mapping methods, our model requires fewer assumptions and also accommodates various machine learning algorithms. Estimation is performed with targeted maximum likelihood learning methods. We demonstrate our semiparametric targeted learning approach in a simulation study and a well-studied barley dataset.

A Note On The Control Function Approach With An Instrumental Variable And A Binary Outcome, Eric Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Simple Regression-Based Approach To Account For Survival Bias In Birth Outcomes Research, Eric J. Tchetgen Tchetgen, Kelesitse Phiri, Roger Shapiro

Harvard University Biostatistics Working Paper Series

No abstract provided.

Entering The Era Of Data Science: Targeted Learning And The Integration Of Statistics And Computational Data Analysis, Mark J. Van Der Laan, Richard J.C.M. Starmans

U.C. Berkeley Division of Biostatistics Working Paper Series

This outlook article will appear in Advances in Statistics and it reviews the research of Dr. van der Laan's group on Targeted Learning, a subfield of statistics that is concerned with the construction of data adaptive estimators of user-supplied target parameters of the probability distribution of the data and corresponding confidence intervals, aiming to only rely on realistic statistical assumptions. Targeted Learning fully utilizes the state of the art in machine learning tools, while still preserving the important identity of statistics as a field that is concerned with both accurate estimation of the true target parameter value and assessment of …

Control Function Assisted Ipw Estimation With A Secondary Outcome In Case-Control Studies, Tamar Sofer, Marilyn C. Cornelis, Peter Kraft, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

Statistical Modeling And Prediction Of Hiv/Aids Prognosis: Bayesian Analyses Of Nonlinear Dynamic Mixtures, Xiaosun Lu

USF Tampa Graduate Theses and Dissertations

Statistical analyses and modeling have contributed greatly to our understanding of the pathogenesis of HIV-1 infection; they also provide guidance for the treatment of AIDS patients and evaluation of antiretroviral (ARV) therapies. Various statistical methods, nonlinear mixed-effects models in particular, have been applied to model the CD4 and viral load trajectories. A common assumption in these methods is all patients come from a homogeneous population following one mean trajectories. This assumption unfortunately obscures important characteristic difference between subgroups of patients whose response to treatment and whose disease trajectories are biologically different. It also may lack the robustness against population heterogeneity …

Association Between Class Iii Obesity (Bmi Of 40-59 Kg/M2) And Mortality: A Pooled Analysis Of 20 Prospective Studies, Cari M. Kitahara, Alan J. Flint, Amy Berrington De Gonzalez, Leslie Bernstein, Michelle Brotzman, Kim Robien, +30 Additional Authors

Epidemiology Faculty Publications

Background

The prevalence of class III obesity (body mass index [BMI]≥40 kg/m2) has increased dramatically in several countries and currently affects 6% of adults in the US, with uncertain impact on the risks of illness and death. Using data from a large pooled study, we evaluated the risk of death, overall and due to a wide range of causes, and years of life expectancy lost associated with class III obesity.

Methods and Findings

In a pooled analysis of 20 prospective studies from the United States, Sweden, and Australia, we estimated sex- and age-adjusted total and cause-specific mortality rates (deaths per …

Super-Learning Of An Optimal Dynamic Treatment Rule, Alexander R. Luedtke, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We consider the estimation of an optimal dynamic two time-point treatment rule defined as the rule that maximizes the mean outcome under the dynamic treatment, where the candidate rules are restricted to depend only on a user-supplied subset of the baseline and intermediate covariates. This estimation problem is addressed in a statistical model for the data distribution that is nonparametric, beyond possible knowledge about the treatment and censoring mechanisms. We propose data adaptive estimators of this optimal dynamic regime which are defined by sequential loss-based learning under both the blip function and weighted classification frameworks. Rather than \textit{a priori} selecting …

Targeted Learning Of The Mean Outcome Under An Optimal Dynamic Treatment Rule, Mark J. Van Der Laan, Alexander R. Luedtke

U.C. Berkeley Division of Biostatistics Working Paper Series

We consider estimation of and inference for the mean outcome under the optimal dynamic two time-point treatment rule defined as the rule that maximizes the mean outcome under the dynamic treatment, where the candidate rules are restricted to depend only on a user-supplied subset of the baseline and intermediate covariates. This estimation problem is addressed in a statistical model for the data distribution that is nonparametric beyond possible knowledge about the treatment and censoring mechanism. This contrasts from the current literature that relies on parametric assumptions. We establish that the mean of the counterfactual outcome under the optimal dynamic treatment …

Predicting The Future Subject's Outcome Via An Optimal Stratification Procedure With Baseline Information, Florence H. Yong, Lu Tian, Sheng Yu, Tianxi Cai, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Tissue Triage And Freezing For Models Of Skeletal Muscle Disease, Hui Meng, Paul M. L. Janssen, Robert W. Grange, Lin Yang, Alan H. Beggs, Lindsay C. Swanson, Stacy A. Cossette, Alison Frase, Martin K. Childers, Henk Granzier, Emanuela Gussoni, Michael W. Lawlor

Biostatistics Faculty Publications

Skeletal muscle is a unique tissue because of its structure and function, which requires specific protocols for tissue collection to obtain optimal results from functional, cellular, molecular, and pathological evaluations. Due to the subtlety of some pathological abnormalities seen in congenital muscle disorders and the potential for fixation to interfere with the recognition of these features, pathological evaluation of frozen muscle is preferable to fixed muscle when evaluating skeletal muscle for congenital muscle disease. Additionally, the potential to produce severe freezing artifacts in muscle requires specific precautions when freezing skeletal muscle for histological examination that are not commonly used when …

Trends And Determinants Of Up-To-Date Status With Colorectal Cancer Screening In Tennessee, 2002-2008, Sreenivas P. Veeranki, Shimin Zheng

ETSU Faculty Works

BACKGROUND:

Screening rates for colorectal cancer (CRC) are increasing nationwide including Tennessee (TN); however, their up-to-date status is unknown. The objective of this study is to determine the trends and characteristics of TN adults who are up-to-date status with CRC screening during 2002-2008.

METHODS:

We examined data from the TN Behavioral Risk Factor Surveillance System for 2002, 2004, 2006 and 2008 to estimate the proportion of respondents aged 50 years and above who were up-to-date status with CRC screening, defined as an annual home fecal occult blood test and/or sigmoidoscopy or colonoscopy in the past 5 years. We identified trends …

Rationale, Design, And Baseline Characteristics Of A Randomized, Placebo-Controlled Cardiovascular Outcome Trial Of Empagliflozin (Empa-Reg Outcometm), Bernard Zinman, Silvio E. Inzucchi, John M. Lachin, Christoph Wanner, Roberto Ferrari, David Fitchett, Erich Bluhmki, Stefan Hantel, Joan Kempthorne-Rawson, Jennifer Newman, Odd Erik Johansen, Hans Juergen Woerle, Uli C. Broedl

Epidemiology Faculty Publications

Background

Evidence concerning the importance of glucose lowering in the prevention of cardiovascular (CV) outcomes remains controversial. Given the multi-faceted pathogenesis of atherosclerosis in diabetes, it is likely that any intervention to mitigate this risk must address CV risk factors beyond glycemia alone. The SGLT-2 inhibitor empagliflozin improves glucose control, body weight and blood pressure when used as monotherapy or add-on to other antihyperglycemic agents in patients with type 2 diabetes. The aim of the ongoing EMPA-REG OUTCOMETM trial is to determine the long-term CV safety of empagliflozin, as well as investigating potential benefits on microvascular outcomes.

Methods

Patients who …

A 2-Step Penalized Regression Method For Family-Based Next-Generation Sequencing Association Studies, Xiuhua Ding, Shaoyong Su, Kannabiran Nandakumar, Xiaoling Wang, David W. Fardo

Biostatistics Faculty Publications

Large-scale genetic studies are often composed of related participants, and utilizing familial relationships can be cumbersome and computationally challenging. We present an approach to efficiently handle sequencing data from complex pedigrees that incorporates information from rare variants as well as common variants. Our method employs a 2-step procedure that sequentially regresses out correlation from familial relatedness and then uses the resulting phenotypic residuals in a penalized regression framework to test for associations with variants within genetic units. The operating characteristics of this approach are detailed using simulation data based on a large, multigenerational cohort.

Modeling Of Multivariate Longitudinal Phenotypes In Family Genetic Studies With Bayesian Multiplicity Adjustment, Lili Ding, Brad G. Kurowski, Hua He, Eileen S. Alexander, Tesfaye B. Mersha, David Fardo, Xue Zhang, Valentina V. Pilipenko, Leah Kottyan, Lisa J. Martin

Biostatistics Faculty Publications

Genetic studies often collect data on multiple traits. Most genetic association analyses, however, consider traits separately and ignore potential correlation among traits, partially because of difficulties in statistical modeling of multivariate outcomes. When multiple traits are measured in a pedigree longitudinally, additional challenges arise because in addition to correlation between traits, a trait is often correlated with its own measures over time and with measurements of other family members. We developed a Bayesian model for analysis of bivariate quantitative traits measured longitudinally in family genetic studies. For a given trait, family-specific and subject-specific random effects account for correlation among family …

Genetic Analysis Workshop 18: Methods And Strategies For Analyzing Human Sequence And Phenotype Data In Members Of Extended Pedigrees, Heike Bickeböller, Julia N. Bailey, Joseph Beyene, Rita M. Cantor, Heather J. Cordell, Robert C. Culverhouse, Corinne D. Engelman, David W. Fardo, Saurabh Ghosh, Inke R. König, Justo Lorenzo Bermejo, Phillip E. Melton, Stephanie A. Santorico, Glen A. Satten, Lei Sun, Nathan L. Tintle, Andreas Ziegler, Jean W. Maccluer, Laura Almasy

Biostatistics Faculty Publications

Genetic Analysis Workshop 18 provided a platform for developing and evaluating statistical methods to analyze whole-genome sequence data from a pedigree-based sample. In this article we present an overview of the data sets and the contributions that analyzed these data. The family data, donated by the Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Ethnic Samples Consortium, included sequence-level genotypes based on sequencing and imputation, genome-wide association genotypes from prior genotyping arrays, and phenotypes from longitudinal assessments. The contributions from individual research groups were extensively discussed before, during, and after the workshop in theme-based discussion groups before being submitted …