Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

DEVELOPMENT OF NOVEL METHODS TO MINIMIZE THE IMPACT OF SEQUENCING ERRORS IN THE NEXT-GENERATION SEQUENCING DATA ANALYSIS

Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

The Comprehensive Assessment of Leadership for Learning: A Next Generation Formative Evaluation and Feedback System

Recent developments in federal policy have prompted the creation of state evaluation frameworks for principals and teachers that hold educators accountable for effective practices and student outcomes. These changes have created a demand for formative evaluation instruments that reflect current accountability pressures and can be used by schools to focus school improvement and leadership development efforts. The Comprehensive Assessment of Leadership for Learning (CALL) is a next generation, 360-degree on-line assessment and feedback system that reflect best practices in feedback design. Some unique characteristics of CALL include a focus on: leadership distributed throughout the school rather than as carried out by an individual leader; assessment of leadership tasks rather than perceptions of leadership practice; a focus on larger complex systems of middle and high school; and transparency of assessment design. This paper describes research contributing to the design and validation of the CALL survey instrument.

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.

Identification of genes associated with quantitative traits involved in cardiovascular disease and lipoprotein metabolism

Cardiovascular disease (CVD) is a threat to public health. It has been reported to be the leading cause of death in United States. The invention of next generation sequencing (NGS) technology has revolutionized the biomedical research. To investigate NGS data of CVD related quantitative traits would contribute to address the unknown etiology and disease mechanism of CVD. NHLBI's Exome Sequencing Project (ESP) contains CVD related phenotypes and their associated NGS exomes sequence data. Initially, a subset of next generation sequencing data consisting of 13 CVD-related quantitative traits was investigated. Only 6 traits, systolic blood pressure (SBP), diastolic blood pressure (DBP), height, platelet counts, waist circumference, and weight, were analyzed by functional linear model (FLM) and 7 currently existing methods. FLM outperformed all currently existing methods by identifying the highest number of significant genes and had identified 96, 139, 756, 1162, 1106, and 298 genes associated with SBP, DBP, Height, Platelet, Waist, and Weight respectively. ^

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^

That Wall is Around My Heart: Family Centered Practice

The author uses a clinical case study, in which he works with a teenager and his adoptive parents to illustrate how placement and adoption decisions can provide physical safety while at the same time exacerbating and extending overlooked and destructive effects of child abuse. The case study highlights the continuing impact of childhood trauma on the interpersonal patterns of behavior within the family, whether biological, kinship, foster or adoptive. The tendency for patterns of aggression and reactivity to be repeated by the victim and his or her caregivers in a foster or adoptive home, and then to extend into the next generation, is an integral aspect of the cycle of child abuse and underscores a critical challenge for skilled and patient staff in family-based service programs.

What is Family Preservation and Why Does it Matter?

This paper describes competing ideas about family preservation, defined both as a defined program of social services and a philosophical approach to helping troubled families. A straightforward definition has become almost impossible because the phrase has taken on so many different meanings, provoking controversy about its "real" meaning and value. Indeed, "family preservation" has become the proverbial elephant whose splendors and horrors are described with great certainty by those impressed by only one of its aspects. While skirmishes between "child savers" and "family preservers" have been part of the child welfare field since its beginning at the turn of the last century, recent debates over family preservation have been especially heated, generating more confusion and animosity than might be expected from the ranks of the small and usually mild-mannered social work profession. The debate is so heated that the director of one of the nation's largest child welfare agencies said recently that he is afraid to "even use the two words on the same page." <1> While the debate about the value of family preservation is unresolved, experimentation with different approaches to service delivery over the last two decades has helped to lay the groundwork for a resurgence of interest in family and community-centered reforms. Better understanding of the family preservation "debates" may be helpful if these reforms are to be successful over the long term. The paper discusses the competing ideas, values, and perceptions that have led observers to their different understandings of family preservation. It briefly chronicles the history of child welfare and examines key theories that have helped lay the groundwork for the resurgence of interest in family-centered services. It concludes with observations about how the competing values at stake in family preservation may affect the next generation of reforms.

Caspase 8: Mediating the effects of a novel proteasome inhibitor, NPI-0052

Targeting the proteasome with the sole FDA approved proteasome inhibitor (PI), bortezomib, has been fruitful in specific cancers. Its success has generated an interest in next-generation PIs that might have a therapeutic advantage in cancers, such as leukemia, where bortezomib monotherapy was less effective. This study focuses on a novel, clinically relevant PI, NPI-0052. Experiments show that NPI-0052 targets chymotrypsin- and caspase-like activities more potently than the trypsin-like activity in leukemia cells. NPI-0052 induced apoptosis, as determined by caspase-3 activation and DNA fragmentation. Using caspase inhibitors and caspase-8 (I9.2) or FADD (I2.1) deficient cells revealed that caspase-8 was essential for NPI-0052-induced apoptosis. NPI-0052 killed cells via a caspase-8-tBid-mitochondrial pathway, relying on caspase-8, whereas bortezomib relies on several caspases. NPI-0052 increased reactive oxygen species (ROS) levels, which contributed towards cytotoxicity since an antioxidant conferred protection. To improve the clinical efficacy of PIs, NPI-0052 was combined with epigenetic anti-cancer agents, histone deacetylase inhibitors (HDACi). NPI-0052 with MS-275 or vorinostat (FDA approved HDACi), synergistically induced apoptosis more effectively than an HDACi/bortezomib regimen in Jurkat cells. Caspase-8 and ROS contributed towards NPI-0052/HDACi cytotoxicity and caspase-8 mediated superoxide production by NPI-0052 or NPI-0052/HDACi. The proximal targets of these agents: proteasome activity and histone acetylation were examined to determine if they contributed towards synergistic effects. HDACi targeted proteasomal β subunits and corresponding catalytic activities responsible for degrading proteins. Immunoblotting showed increases in histone-H3 expression and its acetylation with NPI-0052 or NPI-0052/HDACi in Jurkat and primary cells. Importantly, the hyper-acetylation by NPI-0052 was not detected with bortezomib, suggesting that this effect may be unique to NPI-0052. An antioxidant attenuated histone-H3 expression and acetylation induced by NPI-0052 alone or with HDACi. Furthermore, the hyper-acetylation by NPI-0052 relied on caspase-8. These novel results show that a PI is eliciting classical epigenetic alterations, demonstrated by hyper-acetylation of histone-H3. This alteration was oxidant and caspase-8 dependent. Overall, results reveal that caspase-8 mediates many effects induced by NPI-0052. Data show overlapping activities by NPI-0052 and HDACi which are contributing, along with caspase-8 activation and oxidative stress, to cytotoxic interactions in leukemia cells, reinforcing the potential clinical utility of combining these two compounds. ^

Introduction to disaster epidemiology for public health personnel

There has been a renewed interest in disaster epidemiology after the World Trade Center and Pentagon terrorist attacks of 2001, the devastation of Hurricane Katrina and the overwhelming loss of life that resulted from the tsunami that originated in the Indian Ocean and struck Indonesia and other adjacent countries on December 26, 2004. Institutions that have accepted the challenge of training the next generation of public health professionals as well as to continue the education of the dedicated professionals already serving in public health fields have a responsibility to train practitioners in the basic principles of disaster epidemiology as well as in practical applications of these principles. This culminating experience project involved developing an on-line course complete with the background information as well as relevant case studies that can be used as a curriculum for an introductory course in disaster epidemiology. ^