DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

Characterization of Borrelia burgdorferi Gene Product BBD18 for Its Role(s) in Pathogen Biology and Infectivity

bbd18 is a differentially expressed Borrelia burgdorferi gene that is transcribed at almost undetectable levels in spirochetes grown in vitro but dramatically upregulated during tick infection. The gene also displays low yet detectable expression at various times in tissues of murine hosts. As the gene product bears no homology to known proteins, its biological significance remains enigmatic. To understand the gene function, we created isogenic bbd18-deletion mutants as well as genetically-complemented isolates from an infectious wild-type B. burgdorferi strain. Compared to parental isolates, bbd18 mutants - but not complemented spirochetes - displayed slower in vitro growth. The bbd18 mutants also reflect significantly reduced ability to persist or remain undetectable both in immunocompetent and SCID mice, yet were able to survive in ticks. This suggests BBD18 function is essential in mammalian hosts but redundant in the arthropod vector. Notably, although bbd18 expression and in vitro growth defects are restored in the complemented isolates, their phenotype is similar to the mutants - being unable to persist in mice but able to survive in ticks. Despite low expression in cultured wild-type B. burgdorferi, bbd18 deletion downregulated several genes. Interestingly, expression of some, including ospD and bbi39, could be complemented, while that of others could not be restored via bbd18 re-expression. Correspondingly, bbd18 mutants displayed altered production of several proteins, and similar to RNA levels, some were restored in the bbd18 complement and others not. To understand how bbd18 deletion results in apparently permanent and noncomplementable phenotypic defects, we sought to genetically disturb the DNA topology surrounding the bbd18 locus without deleting the gene. Spirochetes with an antibiotic cassette inserted downstream of the gene, between bbd17 and bbd18, were significantly attenuated in mice, while a similar upstream insertion, between bbd18 and bbd19, did not affect infectivity, suggesting that an unidentified cis element downstream of bbd18 may encode a virulence-associated factor critical for infection.

Cortisol Awakening Response in Preschoolers and Depression Risk: Relations with Maternal History of Depression and Child Temperament

Increasing research suggests that elevations in the cortisol awakening response (CAR), the natural increase of cortisol 30 to 40 minutes after waking, may serve as a vulnerability marker for depression. However, existing studies have focused on adolescence and adulthood; very little is known about the CAR in early childhood and the factors that are associated with it. The current study aimed to examine the validity of the CAR as a potential early-emerging vulnerability marker for depression in a sample of preschool-age children. We examined associations between the CAR and two well-established risk factors for depression: maternal psychopathology and early child temperament (high negative emotionality (NE) and/or low positive emotionality (PE)). The sample consisted of 146 preschool-age children, of whom 71 (49.3%) had a biological mother with a history of depression and 65 (45.5%) had a biological mother with a history of anxiety. To assess the CAR, salivary cortisol samples were collected from the child upon waking, 30 and 45 minutes post-waking on two weekdays. Children’s CAR was examined as the total volume of cortisol secreted (AUCg) and the total increase in cortisol (AUCi) across waking. Evening cortisol was collected 30 minutes before bedtime. Child temperament was assessed using observational laboratory measures. Maternal depression and anxiety were assessed with clinical interviews. Associations with children’s CAR, as indicated by AUCg or AUCi, appeared to be specific to maternal current psychopathology and symptoms of anhedonia. Additionally, we observed significant interactions for both maternal lifetime and current depression and anxiety, in combination with child NE and PE, on elevated evening cortisol levels and flattened diurnal cortisol rhythms, indicating altered patterns of basal cortisol activity in offspring. Our study contributes to the limited but growing knowledge on the development of the CAR in preschool age children and as a marker of early risk. Findings suggest that there is a complex interplay between familial risk, affective vulnerability, and their joint effects on neuroendocrine dysfunction in young children, and highlight the need for future research to examine which aspects of the early diurnal rhythm predict the emergence of later depressive illness.

Dual Quorum Quenching Capsules: Disrupting two bacterial communication pathways that lead to virulence

Healthcare Associated Infections (HAIs) in the United States, are estimated to cost nearly $10 billion annually. And, while device-related infections have decreased, the 60% attributed to pneumonia, gastrointestinal pathogens and surgical site infections (SSIs) remain prevalent. Furthermore, these are often complicated by antibacterial resistance that ultimately cause 2 million illnesses and 23,000 deaths in the US annually. Antibacterial resistance is an issue increasing in severity as existing antibiotics are losing effectiveness, and fewer new antibiotics are being developed. As a result, new methods of combating bacterial virulence are required. Modulating communications of bacteria can alter phenotype, such as biofilm formation and toxin production. Disrupting these communications provides a means of controlling virulence without directly interacting with the bacteria of interest, a strategy contrary to traditional antibiotics. Inter- and intra-species bacterial communication is commonly called quorum sensing because the communication molecules have been linked to phenotypic changes based on bacterial population dynamics. By disrupting the communication, a method called ‘quorum quenching’, bacterial phenotype can be altered. Virulence of bacteria is both population and species dependent; each species will secrete different toxic molecules, and total population will affect bacterial phenotype9. Here, the kinase LsrK and lactonase SsoPox were combined to simultaneously disrupt two different communication pathways with direct ties to virulence leading to SSIs, gastrointestinal infection and pneumonia. To deliver these enzymes for site-specific virulence prevention, two naturally occurring polymers were used, chitosan and alginate. Chitosan, from crustacean shells, and alginate, from seaweed, are frequently studied due to their biocompatibility, availability, self-assembly and biodegrading properties and have already been verified in vivo for wound-dressing. In this work, a novel functionalized capsule of quorum quenching enzymes and biocompatible polymers was constructed and demonstrated to have dual-quenching capability. This combination of immobilized enzymes has the potential for preventing biofilm formation and reducing bacterial toxicity in a wide variety of medical and non-medical applications.