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Translating Mouse Systems Genetics to Discovery in Human Disease
Full text linkThis dissertation is the culmination of my graduate studies in the laboratory of Jake Lusis at UCLA. The research presented here utilizes systems genetics studies performed in mice to aid in discovery in human disease in three separate studies. A significant portion of disease-oriented research is performed in mice, but a major criticism from the medical community is that laboratory mice are generally inbred and thus have no genetic variation among individuals. Almost 15 years ago, the Lusis lab developed a novel genetic resource for association analysis in the mouse called the Hybrid Mouse Diversity Panel (HMDP). The HMDP is a panel of inbred mouse strains that was developed for performing association studies with adequate statistical power and resolution for mapping of complex traits. Mouse genome wide association studies (GWAS) studies are a powerful tool and can be performed relatively easily, but translating the data obtained from these studies to human disease is still in its infancy. My dissertation work reveals three different novel approaches to the utilization of data from GWAS studies performed on the HMDP for translation into human disease processes, namely cardiovascular disease. The first study utilizes novel genetic signatures in murine macrophages to predict disease incidence and survival in humans. The second study utilizes a traditional GWAS to candidate gene discovery to elucidate the mechanisms underlying cardiac remodeling in humans. Lastly, the third study utilizes mouse GWAS data for novel heart failure biomarker discovery in humans. As an introduction to this dissertation, Chapter 1 briefly summarizes the history of GWAS in mice using the HMDP and GWAS in humans. Chapter 2 is a completed and accepted first-author manuscript entitled “Natural diversity reveals macrophage activation spectra predictive of inflammation and cancer survival.” Chapter 3 explores the role of CD200, a candidate gene obtained from a large heart failure GWAS study in mice, and it’s receptor, CD200R1 in cardiac homeostasis and injury. Chapter 4 describes a novel approach to biomarker discovery for human heart failure using data from a large heart failure GWAS study. Chapter 5 is a departure from mouse systems genetics. In this chapter, I describe the strengths and pitfalls of exome sequencing. In addition, I describe two cases of rare cardiovascular disease in which exome sequencing is utilized to find causal variants of disease. Ultimately, I’d like to use what I’ve learned in my studies of mouse genetics and translate this to discovery in human disease. In conclusion, this dissertation work contributes significant findings to the expanding knowledge of utilizing mouse GWAS for discovery in human disease
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The Impact of Voluntary Running on Mitochondria in Liver and Skeletal Muscle
Full text linkExercise is an effective means of preventing and treating metabolic disorders such as insulin resistance. The mechanism by which exercise prevents complex diseases, however, is not well understood. Mitochondria are intracellular organelles intimately linked with metabolic disorders. Mitochondria are unique in that they possess their own, albeit incomplete, genetic material termed mitochondrial DNA (mtDNA). The primary objectives of this thesis were to: (1) determine the impact of voluntary aerobic exercise upon mtDNA in various metabolic organs and (2) elucidate the possible mechanism(s) by which exercise influences mtDNA. To determine mitochondrial abundance, mtDNA is used as a surrogate readout. We subjected female mice from the Hybrid Mouse Diversity Panel (HMDP) to two separate lifestyles, with or without voluntary aerobic exercise. In skeletal muscle and liver, exercised animals showed a significant increase in mtDNA content compared to the unexercised sedentary group. Average running speed was positively correlated with mtDNA content in skeletal muscle. Candidate genes that may be involved in the increased mtDNA content have also been identified. Future research should focus on thorough in-depth studies examining the genes involved in the mechanism(s) by which this increase occurs and if such increase confer the health benefits associated with exercise such as reductions in liver fats using genome-wide association studies
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Utilizing Systems Genetics Approaches to Identify Novel Molecular Mechanisms in Cardiovascular Diseases
Full text linkDespite the success of focused, reductionist approaches in characterizing the pathophysiology of cardiovascular diseases (CVDs), current estimates predict that 24 million deaths annually will be due to CVDs by 2030. Emphasizing the use of genetic variation in combination with mathematical modeling and integration of next generation –omics profiling technologies, systems genetics characterizes the flow of biological information in physiologic and pathologic states to allow investigators to understand the molecular interactions in a system. To assess the feasibility of systems genetics based methodologies in identifying novel interactions that contribute to CVD pathology I have used a combination of animal and cell culture models to recapitulate key processes involved in two CVDs: atherosclerosis and congestive heart failure.Atherosclerosis, a systemic disorder characterized by the narrowing of arteries is the underlying cause of the majority of clinical cardiovascular events. Formation of the atherosclerotic plaque is driven by chronic endothelial activation from exposure to oxidized phospholipids that accumulate within the vessel wall. Using systems approaches we have identified miRs-21-3p and -27a-5p as novel regulators of NF-κB signaling, a crucial pathway in mediating endothelial activation. Congestive heart failure (CHF) is a CVD that develops in part as a complication of atherosclerosis that is characterized by the inability of the heart to pump blood. Using a novel genetic screening panel in mouse in combination with system based approaches, I have identified and characterized the function of numerous novel genes that modulate CHF phenotypes such as cardiac fibrosis (Abcc6), left ventricular mass (Myh14) and cardiac hypertrophy (Adamts2)
Trends Genet
Full text linkGenome-wide association studies (GWAS) from the past several years have provided the first unbiased evidence of the genes contributing to common cardiovascular disease traits in European and some Asian populations. The results not only confirmed the importance of prior knowledge, such as the central role of lipoproteins, but also revealed that there is still much to learn about the underlying mechanisms of this disease, as most of the associated genes do not appear to be involved in pathways previously connected to atherosclerosis. In this review, I focus on the common forms of the disease and look at both human and animal model studies. I summarize what was known before GWAS, highlight how the field has been changed by GWAS, and discuss future considerations, such as the limitations of GWAS and strategies that may lead to a more complete, mechanistic understanding of atherosclerosis.R01 HL094322/HL/NHLBI NIH HHS/United StatesDP3 D094311/DP/NCCDPHP CDC HHS/United StatesP01 HL305685/HL/NHLBI NIH HHS/United StatesR21 HL110667/HL/NHLBI NIH HHS/United StatesP01 HL28481/HL/NHLBI NIH HHS/United StatesDP3 DK094311/DK/NIDDK NIH HHS/United StatesP01 HL028481/HL/NHLBI NIH HHS/United StatesR01 HL0943221/HL/NHLBI NIH HHS/United StatesR21 HL110667-01/HL/NHLBI NIH HHS/United States1R01 GM0956561/GM/NIGMS NIH HHS/United StatesP01 HL030568/HL/NHLBI NIH HHS/United StatesR01 GM095656/GM/NIGMS NIH HHS/United States2013-06-01T00:00:00Z22480919PMC3362664903
Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis.
No full textLevels of certain circulating short-chain dicarboxylacylcarnitine (SCDA), long-chain dicarboxylacylcarnitine (LCDA) and medium chain acylcarnitine (MCA) metabolites are heritable and predict cardiovascular disease (CVD) events. Little is known about the biological pathways that influence levels of most of these metabolites. Here, we analyzed genetics, epigenetics, and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis. Using genomewide association in the CATHGEN cohort (N = 1490), we observed associations of several metabolites with genetic loci. Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum (ER) stress (USP3, HERC1, STIM1, SEL1L, FBXO25, SUGT1) These findings were validated in a second cohort of CATHGEN subjects (N = 2022, combined p = 8.4x10-6-2.3x10-10). Importantly, variants in these genes independently predicted CVD events. Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated (BRSK2 and HOOK2). Expression quantitative trait loci (eQTL) pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system (UPS) arm. Moreover, culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease, induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP. Thus, our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis, and identifies novel genetic loci associated with CVD event risk
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Gene expression of cell types present in the vascular wall during the initiation and progression of atherosclerosis
Full text linkA key element of atherosclerosis, the primary cause of coronary artery disease (CAD), is chronic inflammation of the vessel wall. Identifying the gene expression of the cells present in the vessel wall during atherogenesis can clarify these events and provide new research possibilities. The work presented here characterizes a putative transcription factor that contributes to atherosclerosis, identifies candidate genes involved in the activation of endothelial cells, and defines the expression patterns of CAD GWAS candidate genes in mouse vascular cells. Zhx2, a putative transcription factor, was identified as a gene controlling plasma lipid levels using congenic mice and fine-mapping. Liver-specific Zhx2 transgenic mice on a Zhx-null background exhibited a corrected plasma lipid profile, confirming Zhx2 as the gene controlling the plasma lipid phenotype. Male Zhx2-null mice had atherosclerotic lesions nine times smaller than mice with a wild-type Zhx2 allele, a large effect that could not be fully explained by their plasma lipid profiles. Treatment of macrophages with the pro-inflammatory factor LPS elicited a strong increase in Zhx2 transcript, suggesting involvement in the inflammatory response. A bone marrow transplant of Zhx2-null hematopoietic stem cells into Zhx2 wild-type mice resulted in a more than 4-fold reduction in atherosclerotic lesion size, supporting a role for Zhx2 in the chronic immune response accompanying atherosclerosis. Endothelial cells are a central component in the initiation and progression of atherosclerosis, and the study of their expression profile could provide valuable data. Since the cell culture of mouse aortic endothelial cells (MAECs) has been challenging, we identified an alternate method for the isolation of RNA from these cells. Microarray analysis of these transcripts identified 14 differentially expressed genes in pre-lesioned MAECs, eight of which have not been previously described in atherosclerosis. This method has also made it feasible to collect RNA samples from distinct cell types present in the vessel wall during atherosclerosis. Recent genome wide association studies on CAD have identified loci representing 56 candidate genes. We used quantitative PCR to identify the expression levels of these genes in each atherosclerotic cell type and report the results
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Heart Failure Genetics in Mice and Men
Full text linkThe genetics of heart failure is complex. In familial cases of cardiomyopathy, where mutations of large effects predominate in theory, genetic testing using a gene panel of up to 76 genes returned negative results in about half of the cases. In common forms of heart failure (HF), where a large number of genes with small to modest effects are expected to modify disease, only a few candidate genomic loci have been identified through genome-wide association (GWA) analyses in humans. We aimed to use exome sequencing to rapidly identify rare causal mutations in familial cardiomyopathy cases and effectively filter and classify the variants based on family pedigree and family member samples. We identified a number of existing variants and novel genes with great potential to be disease causing. On the other hand, we also set out to understand genetic factors that predispose to common late-onset forms of heart failure by performing GWA in the isoproterenol-induced HF model across the Hybrid Mouse Diversity Panel (HMDP) of 105 strains of mice. We performed fine phenotyping using serial echocardiograms and controlled for environmental heterogeneity in the experimental setting. As a result, we achieved high heritability estimates of 64% to 84% for all cardiac traits and had superior power for mapping HF-related trait, compared to human studies. Association analyses of cardiac traits, corrected for population structure and multiple comparisons, revealed genome-wide significant loci across the spectrum of cardiac traits. Cardiac tissue gene expression profiling, expression quantitative trait loci, expression-phenotype correlation, and coding sequence variation analyses were performed to prioritize candidate genes and to generate hypotheses for downstream mechanistic studies. Future directions will be to further bridge the gap of understanding between rare Mendelian and common cardiovascular diseases, which together will have wide spread therapeutic implications in delaying or reversing HF progression in human populations
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Liver-Heart Crosstalk Mechanisms in Heart Failure
No full textThis work encompasses the discovery and assessment of a liver-secreted protein that plays an important role in the development of a common form of heart failure. We also include a chapter on the development of nuclei isolation methodology for the purpose of applying single-nuclei RNA sequencing (snRNAseq) to some related cardiovascular projects. Chapter 1 highlights the identification of a novel liver-secreted factor, Hepatocyte Growth Factor Activator (HGFAC), that regulates the heart in an endocrine manner. In a mouse models of both heart failure with preserved ejection fraction (HFpEF) and reduced ejection fraction (HFrEF), overexpression of Hgfac in the liver exacerbates heart hypertrophy and diastolic dysfunction. Conversely, silencing Hgfac using shRNA was able to reverse HFpEF in mice. We show that HGFAC promotes HFpEF by activating circulating hepatocyte growth factor (HGF), which then binds to the c-MET receptor and activates the PI3K/AKT pathway in the heart. This work identifies HGFAC as an endocrine factor that aggravates heart failure with therapeutic potential in humans. Chapter 2 details an optimized protocol for tissue nuclei isolation and subsequent single-nuclei RNA sequencing analysis. The methodology employs a systematic approach beginning with precise tissue mincing in specialized media, followed by gentle mechanical dissociation using a glass dounce homogenizer. The protocol incorporates multiple filtration and purification steps, including debris removal and size-selective straining, to ensure high-quality nuclear preparations. The isolated nuclei are then processed using the 10x Genomics platform for library construction and sequenced on NovaSeq instrumentation. Computational analysis utilizes current versions of CellRanger and Seurat packages for alignment, quality control, and differential gene expression analysis, with rigorous statistical testing and pathway enrichment analysis to elucidate biological significance. This standardized approach enables reliable transcriptional profiling at single-nucleus resolution across diverse tissue types, providing a valuable tool for investigating cellular heterogeneity in cardiovascular research. The utility of this methodology is demonstrated through collaborative studies examining transcriptional changes in various experimental contexts including heart failure and abdominal aortic aneurysms, successfully generating high-quality nuclear transcriptomes from adult heart, neonatal ventricles, and aortic tissue
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A Systems Genetics Approach to the Identification of Causal Genes in Heart Failure Using a Large Mouse Panel
Full text linkHeart failure (HF) accounts for 1 in 9 deaths in the United States and is the leading cause of hospitalization for people over the age of 65 and the incidence of HF is predicted to rise over the coming years. The complexity which underlies common forms of HF has hindered the study of the disease in humans, and approaches, such as genome-wide association studies (GWAS), have had only modest success in identifying genes which are related to this disease. Here we describe the use of a panel of mice to facilitate the study of this complex disorder, reducing heterogeneity and facilitating systems-level approaches.We used the beta-adrenergic agonist isoproterenol to induce HF in 105 unique strains drawn from the Hybrid Mouse Diversity Panel, a novel mouse resource population for the analysis of complex traits. Our first study reports the results of a GWAS on heart weights, cardiac fibrosis and other surrogate traits relevant to HF. Among the 32 significant loci, we identified several strong candidates which had previously been shown to contribute to mendelian forms of cardiomyopathy. We were also able to validate two novel candidate genes, the orphan transporter Abcc6, and the long noncoding RNA Miat, using gene targeting, transgenic and in vitro approaches.As part of our systems genetics approach, we developed a novel gene network construction algorithm, which improves on prior methods by allowing non-linear interactions and the ability for genes to operate in multiple modules at once. We were able to demonstrate using previously published data that our results either matched or exceeded another well-known network construction algorithm. In a subsequent study, we applied this method to transcriptomes taken from the HF study. We identified a module of 41 genes which significantly regulates the response of the heart to isoproterenol and HF and which contains several genes of interest such as Lgals3, a diagnostic marker for human HF.Our results provide a valuable resource toward a better understanding of the pathways and gene-by-environment interactions influencing heart failure
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Leveraging variation in genetically diverse mouse strains to study Metabolic Syndrome phenotypes
Full text linkThe Hybrid Mouse Diversity Panel (HMDP) is a systems genetic resource of over one hundred different mouse strains. The genetic variation and subsequent phenotypic variation between strains in the HMDP encompass a spectrum of metabolic phenotypes from weight gain following a high-fat diet to susceptibility to heart and liver disease. My dissertation research focuses on the analysis of genetic and genomic data originating from multiple HMDP studies for Metabolic Syndrome phenotypes. Firstly, I identified DNA methylation patterns associated with diet-induced obesity that were observed across diverse genetic backgrounds. I then asked whether these epigenetic changes were maintained following weight loss in a subset of strains. Secondly, I characterized novel genes for atherosclerosis, Nnmt, Csf1, and Zhx2. Lastly, I used transcriptional approaches with genetically diverse mouse strains to identify susceptibility mechanisms involved in the development of progressive liver disease phenotypes. Taken together, this body of research encompasses genetic, cell-type, gene expression, and epigenetic approaches to investigate mechanisms involved in obesity, heart, and liver disease
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