Metabolic status differentiates Trp53inp2 function in pressure-overload induced heart failure

Cardiometabolic disorders encompass a broad range of cardiovascular complications associated with metabolic dysfunction. These conditions have an increasing share in the health burden worldwide due to worsening endemic of hypertension, obesity, and diabetes. Previous studies have identified Tumor Protein p53-inducible Nuclear Protein 2 (Trp53inp2) as a molecular link between hyperglycemia and cardiac hypertrophy. However, its role in cardiac pathology has never been determined in vivo. In this study, we generated a cardiac specific knockout model of Trp53inp2 (Trp53inp2-cKO) and investigated the impact of Trp53inp2 inactivation on the pathogenesis of heart failure under mechanic or/and metabolic stresses. Based on echocardiography assessment, inactivation of Trp53inp2 in heart led to accelerated onset of HFrEF in response to pressure-overload, with significantly reduced ejection fraction and elevated heart failure marker genes comparing to the control mice. In contrast, inactivation of Trp53inp2 ameliorated cardiac dysfunction induced by combined stresses of high fat diet and moderate pressure overload (Cardiometabolic Disorder Model). Moreover, Trp53inp2 inactivation led to reduced expression of glucose metabolism genes in lean, pressure-overloaded hearts. However, the same set of genes were significantly induced in the Trp53inp2-cKO hearts under both mechanical and metabolic stresses. In summary, we have demonstrated for the first time that cardiomyocyte Trp53inp2 has diametrically differential roles in the pathogenesis of heart failure and glucose regulation under mechanical vs. mechanical plus metabolic stresses. This insight suggests that Trp53inp2 may exacerbate the cardiac dysfunction during pressure overload injury but have a protective effect in cardiac diastolic function in cardiometabolic disease.

Cardiomyocyte ploidy is dynamic during postnatal development and varies across genetic backgrounds

Somatic polyploidization, an adaptation by which cells increase their DNA content to support growth, is observed in many cell types, including cardiomyocytes. Although polyploidization is believed to be beneficial, progression to a polyploid state is often accompanied by loss of proliferative capacity. Recent work suggests that genetics heavily influence cardiomyocyte ploidy. However, the developmental course by which cardiomyocytes reach their final ploidy state has only been investigated in select backgrounds. Here, we assessed cardiomyocyte number, cell cycle activity, and ploidy dynamics across two divergent mouse strains: C57BL/6J and A/J. Both strains are born and reach adulthood with comparable numbers of cardiomyocytes; however, the end composition of ploidy classes and developmental progression to reach the final state differ substantially. We expand on previous findings that identified Tnni3k as a mediator of cardiomyocyte ploidy and uncover a role for Runx1 in ploidy dynamics and cardiomyocyte cell division, in both developmental and injury contexts. These data provide novel insights into the developmental path to cardiomyocyte polyploidization and challenge the paradigm that hypertrophy is the sole mechanism for growth in the postnatal heart.

Cell-autonomous effect of cardiomyocyte branched-chain amino acid catabolism in heart failure in mice

Parallel to major changes in fatty acid and glucose metabolism, defect in branched-chain amino acid (BCAA) catabolism has also been recognized as a metabolic hallmark and potential therapeutic target for heart failure. However, BCAA catabolic enzymes are ubiquitously expressed in all cell types and a systemic BCAA catabolic defect is also manifested in metabolic disorder associated with obesity and diabetes. Therefore, it remains to be determined the cell-autonomous impact of BCAA catabolic defect in cardiomyocytes in intact hearts independent from its potential global effects. In this study, we developed two mouse models. One is cardiomyocyte and temporal-specific inactivation of the E1α subunit (BCKDHA-cKO) of the branched-chain α-ketoacid dehydrogenase (BCKDH) complex, which blocks BCAA catabolism. Another model is cardiomyocyte specific inactivation of the BCKDH kinase (BCKDK-cKO), which promotes BCAA catabolism by constitutively activating BCKDH activity in adult cardiomyocytes. Functional and molecular characterizations showed E1α inactivation in cardiomyocytes was sufficient to induce loss of cardiac function, systolic chamber dilation and pathological transcriptome reprogramming. On the other hand, inactivation of BCKDK in intact heart does not have an impact on baseline cardiac function or cardiac dysfunction under pressure overload. Our results for the first time established the cardiomyocyte cell autonomous role of BCAA catabolism in cardiac physiology. These mouse lines will serve as valuable model systems to investigate the underlying mechanisms of BCAA catabolic defect induced heart failure and to provide potential insights for BCAA targeted therapy.

Abstract P1113: Ploidy Reversal As A Postnatal Developmental Program In Murine Hearts

Polyploidization is a normal cellular adaptation for a variety of cell types in mammals, including cardiomyocytes (CMs); however, the development of polyploidization understudied. Recent work suggests that genetics contribute to diverse displays of ploidy in the adult murine heart. Therefore, we hypothesized that the developmental progression to reach differing end-states may similarly be affected. Here, we assessed CM endowment, cell cycle, and ploidy temporally across two diverse inbred mouse strains, A/J and C57Bl/6J. Consistent with previous work, C57Bl/6J hearts displayed rapid cell cycle activation in the first postnatal week largely coinciding with the first round of endomitosis. Total CM numbers are relatively unchanged after P7, while final ploidy states are generally constant from P14 on. In contrast, A/J mice displayed depressed cell cycle activation in the first week of life. Polyploidy in A/Js reaches its peak at P21, whereby only ~3.5% of CMs remained mononuclear and diploid. Interestingly, from 3-6 weeks of age, we observed a dramatic expansion of total CM numbers and of the 1x2N subpopulation to ~8%, which could not be explained by proliferation of the residual diploid population. Instead, the expanded diploid population appears to come from a polyploid CM. This finding was confirmed by analysis identifying a population of CMs which had definitively completed cytokinesis by 6 weeks which was not present at 3 weeks. We believe this is the first report of ploidy reversal by a mammalian CM, a phenomenon first observed by the hepatocyte field. Ongoing single nuclear RNA seq is examining the transcriptomic differences between A/J and C57Bl/6J CMs at P21 to identify this unique “primed” population competent to undergo ploidy reversal. Preliminary results from this study suggest that AJ CM nuclei, regardless of their ploidy, are more likely to be in the cell cycle in comparison to C57. Understanding the developmental paths to end state CM endowment and ploidy states can help us understand the biology of organ size and reciprocally can be applied to stimulating regeneration.

Sex differences in heart mitochondria regulate diastolic dysfunction

Heart failure with preserved ejection fraction (HFpEF) exhibits a sex bias, being more common in women than men, and we hypothesize that mitochondrial sex differences might underlie this bias. As part of genetic studies of heart failure in mice, we observe that heart mitochondrial DNA levels and function tend to be reduced in females as compared to males. We also observe that expression of genes encoding mitochondrial proteins are higher in males than females in human cohorts. We test our hypothesis in a panel of genetically diverse inbred strains of mice, termed the Hybrid Mouse Diversity Panel (HMDP). Indeed, we find that mitochondrial gene expression is highly correlated with diastolic function, a key trait in HFpEF. Consistent with this, studies of a "two-hit" mouse model of HFpEF confirm that mitochondrial function differs between sexes and is strongly associated with a number of HFpEF traits. By integrating data from human heart failure and the mouse HMDP cohort, we identify the mitochondrial gene Acsl6 as a genetic determinant of diastolic function. We validate its role in HFpEF using adenoviral over-expression in the heart. We conclude that sex differences in mitochondrial function underlie, in part, the sex bias in diastolic function.

Cerebrovascular insufficiency and amyloidogenic signaling in Ossabaw swine with cardiometabolic heart failure

Individuals with heart failure (HF) frequently present with comorbidities, including obesity, insulin resistance, hypertension, and dyslipidemia. Many patients with HF experience cardiogenic dementia, yet the pathophysiology of this disease remains poorly understood. Using a swine model of cardiometabolic HF (Western diet+aortic banding; WD-AB), we tested the hypothesis that WD-AB would promote a multidementia phenotype involving cerebrovascular dysfunction alongside evidence of Alzheimer’s disease (AD) pathology. The results provide evidence of cerebrovascular insufficiency coupled with neuroinflammation and amyloidosis in swine with experimental cardiometabolic HF. Although cardiac ejection fraction was normal, indices of arterial compliance and cerebral blood flow were reduced, and cerebrovascular regulation was impaired in the WD-AB group. Cerebrovascular dysfunction occurred concomitantly with increased MAPK signaling and amyloidogenic processing (i.e., increased APP, BACE1, CTF, and Aβ40 in the prefrontal cortex and hippocampus) in the WD-AB group. Transcriptomic profiles of the stellate ganglia revealed the WD-AB group displayed an enrichment of gene networks associated with MAPK/ERK signaling, AD, frontotemporal dementia, and a number of behavioral phenotypes implicated in cognitive impairment. These provide potentially novel evidence from a swine model that cerebrovascular and neuronal pathologies likely both contribute to the dementia profile in a setting of cardiometabolic HF.

The right ventricular transcriptome signature in Ossabaw swine with cardiometabolic heart failure: implications for the coronary vasculature

Heart failure (HF) patients with deteriorating right ventricular (RV) structure and function have a nearly twofold increased risk of death compared with those without. Despite the well-established clinical risk, few studies have examined the molecular signature associated with this HF condition. The purpose of this study was to integrate morphological, molecular, and functional data with the transcriptome data set in the RV of a preclinical model of cardiometabolic HF. Ossabaw swine were fed either normal diet without surgery (lean control, n = 5) or Western diet and aortic-banding (WD-AB; n = 4). Postmortem RV weight was increased and positively correlated with lung weight in the WD-AB group compared with CON. Total RNA-seq was performed and gene expression profiles were compared and analyzed using principal component analysis, weighted gene co-expression network analysis, module enrichment analysis, and ingenuity pathway analysis. Gene networks specifically associated with RV hypertrophic remodeling identified a hub gene in MAPK8 (or JNK1) that was associated with the selective induction of the extracellular matrix (ECM) component fibronectin. JNK1 and fibronectin protein were increased in the right coronary artery (RCA) of WD-AB animals and associated with a decrease in matrix metalloproteinase 14 protein, which specifically degrades fibronectin. RCA fibronectin content was correlated with increased vascular stiffness evident as a decreased elastin elastic modulus in WD-AB animals. In conclusion, this study establishes a molecular and transcriptome signature in the RV using Ossabaw swine with cardiometabolic HF. This signature was associated with altered ECM regulation and increased vascular stiffness in the RCA, with selective dysregulation of fibronectin.

Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for "polygenic epistasis"

Background

The majority of quantitative genetic models used to map complex traits assume that alleles have similar effects across all individuals. Significant evidence suggests, however, that epistatic interactions modulate the impact of many alleles. Nevertheless, identifying epistatic interactions remains computationally and statistically challenging. In this work, we address some of these challenges by developing a statistical test for polygenic epistasis that determines whether the effect of an allele is altered by the global genetic ancestry proportion from distinct progenitors.

Results

We applied our method to data from mice and yeast. For the mice, we observed 49 significant genotype-by-ancestry interaction associations across 14 phenotypes as well as over 1,400 Bonferroni-corrected genotype-by-ancestry interaction associations for mouse gene expression data. For the yeast, we observed 92 significant genotype-by-ancestry interactions across 38 phenotypes. Given this evidence of epistasis, we test for and observe evidence of rapid selection pressure on ancestry specific polymorphisms within one of the cohorts, consistent with epistatic selection.

Conclusions

Unlike our prior work in human populations, we observe widespread evidence of ancestry-modified SNP effects, perhaps reflecting the greater divergence present in crosses using mice and yeast.

Many statistical tests which link genetic markers in the genome to differences in traits rely on the assumption that the same polymorphism will have identical effects in different individuals. However, there is substantial evidence indicating that this is not the case. Epistasis is the phenomenon in which multiple polymorphisms interact with one another to amplify or negate each other’s effects on a trait. We hypothesized that individual SNP effects could be changed in a polygenic manner, such that the proportion of as genetic ancestry, rather than specific markers, might be used to capture epistatic interactions. Motivated by this possibility, we develop a new statistical test that allowed us to examine the genome to identify polymorphisms which have different effects depending on the ancestral makeup of each individual. We use our test in two different populations of inbred mice and a yeast panel and demonstrate that these sorts of variable effect polymorphisms exist in 14 different physical traits in mice and 38 phenotypes in yeast as well as in murine gene expression. We use the term “polygenic epistasis” to distinguish these interactions from the more conventional two- or multi-locus interactions.

Matrix Metalloproteinases and Tissue Inhibitors of Metalloproteinases in Extracellular Matrix Remodeling during Left Ventricular Diastolic Dysfunction and Heart Failure with Preserved Ejection Fraction: A Systematic Review and Meta-Analysis

Matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) are pivotal regulators of extracellular matrix (ECM) composition and could, due to their dynamic activity, function as prognostic tools for fibrosis and cardiac function in left ventricular diastolic dysfunction (LVDD) and heart failure with preserved ejection fraction (HFpEF). We conducted a systematic review on experimental animal models of LVDD and HFpEF published in MEDLINE or Embase. Twenty-three studies were included with a total of 36 comparisons that reported established LVDD, quantification of cardiac fibrosis and cardiac MMP or TIMP expression or activity. LVDD/HFpEF models were divided based on underlying pathology: hemodynamic overload (17 comparisons), metabolic alteration (16 comparisons) or ageing (3 comparisons). Meta-analysis showed that echocardiographic parameters were not consistently altered in LVDD/HFpEF with invasive hemodynamic measurements better representing LVDD. Increased myocardial fibrotic area indicated comparable characteristics between hemodynamic and metabolic models. Regarding MMPs and TIMPs; MMP2 and MMP9 activity and protein and TIMP1 protein levels were mainly enhanced in hemodynamic models. In most cases only mRNA was assessed and there were no correlations between cardiac tissue and plasma levels. Female gender, a known risk factor for LVDD and HFpEF, was underrepresented. Novel studies should detail relevant model characteristics and focus on MMP and TIMP protein expression and activity to identify predictive circulating markers in cardiac ECM remodeling.

Abstract MP144: Identification of Epigenetic Regulators of Cardiac Hypertrophy by an Epigenome-wide Association Study in Mice

We previously reported a study of heart failure in a large cohort of inbred mouse strains, the Hybrid Mouse Diversity Panel (HMDP), treated with the beta-adrenergic agonist isoproterenol, which identified over 30 genome-wide significant loci for heart failure-related traits. Our approach combined systems-level tools with the benefits of a curated model organism population to identify genetic variations that drive heart failure.

We now expand this study into the epigenome. Recent research has demonstrated that DNA methylation affects the progression of cardiovascular phenotypes. This research suggests that DNA methylation may serve as an additional marker of genes involved in heart failure-associated phenotypes. Using Reduced Representational Bisulfite Sequencing, we profiled left ventricular tissue samples from 88 strains of the HMDP both before and after isoproterenol challenge (30 mg/kg/day for 21 days). We identified approximately 168,000 CpGs that vary across the panel and associated them with a set of phenotypes in both control and treated animals using the epigenome-wide association study (EWAS) algorithm MACAU. 179 significant associations were recovered at an FDR of 5%, including loci that associated pre-treatment CpG methylation with 19 different post-treatment phenotypes.

By combining these EWAS loci with information from the Wellcome Trust Mouse Genomes Resource and prior work done in the heart failure HMDP, we identify several high-confidence candidate genes, including Coro1a , a gene whose pre-treatment promoter methylation status predicts post-treatment wall thickening and Eprs , which predicts right ventricular weight post-treatment. Mospd3 , a gene that was associated with right ventricular weight post-treatment in both EWAS and GWAS analyses was studied further using neonatal rat ventricular myocytes. This in vitro work demonstrates that Mospd3 knockdown results in reduced cellular hypertrophy and changes to hypertrophy-related gene expression. Further analysis of the EWAS loci using in vitro and in vivo techniques will likely validate additional genes and elucidate how DNA methylation acts to regulate pathways underlying heart failure.

Systems Genetics for Mechanistic Discovery in Heart Diseases

Cardiovascular diseases are the leading cause of death worldwide. Complex diseases with highly heterogenous disease progression among patient populations, cardiovascular diseases feature multifactorial contributions from both genetic and environmental stressors. Despite significant effort utilizing multiple approaches from molecular biology to genome-wide association studies, the genetic landscape of cardiovascular diseases, particularly for the nonfamilial forms of heart failure, is still poorly understood. In the past decade, systems-level approaches based on omics technologies have become an important approach for the study of complex traits in large populations. These advances create opportunities to integrate genetic variation with other biological layers to identify and prioritize candidate genes, understand pathogenic pathways, and elucidate gene-gene and gene-environment interactions. In this review, we will highlight some of the recent progress made using systems genetics approaches to uncover novel mechanisms and molecular bases of cardiovascular pathophysiological manifestations. The key technology and data analysis platforms necessary to implement systems genetics will be described, and the current major challenges and future directions will also be discussed. For complex cardiovascular diseases, such as heart failure, systems genetics represents a powerful strategy to obtain mechanistic insights and to develop individualized diagnostic and therapeutic regiments, paving the way for precision cardiovascular medicine.

Abstract 944: Differential Dna Methylation Co-segregates With the Severity of Heart Failure

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. As a potential epigenetic biomarker, DNA methylation differs between healthy and diseased hearts. However, its association according to disease severity has not yet been studied. Here, we sought to investigate how DNA methylation (DNAm) differs across HF disease severity, and study the use of a DNMT methyltransferase inhibitor RG108 on DNAm and its effect on heart function. A fixed dose of Isoprenaline (ISO), or saline control (SAL), administered to a hybrid mouse diversity panel (HMDP) consisting of 85 classical and recombinant inbred mouse strains produced a range of cardiac hypertrophy and/or LV dilatation. Left ventricles were harvested and subjected to genome-wide cardiac DNAm profiling by Reduced Representation Bisulfite Sequencing (RRBS). Unsupervised clustering of the top 1% most variable CpG methylation segregated strains to their genetic origin. Disregarding strain-specific methylation differences, differential methylation between ISO and SAL unexpectedly categorised mice into mild and severe disease responders. In the severe-responder strain BTBRT, the pharmacological DNMT methyltransferase inhibitor, RG108, rescued disease from ISO-response, with accompanying evidence of gene expression recovery. This work establishes the range of cardiac differential DNAm correlating according to disease severity. It displays the involvement of DNA methylation-dependent gene expression changes that turns out to be unique, despite different mouse strain backgrounds. This gives further proof of principle that cardiac DNAm changes represent novel biomarkers for disease stratification and consequent targeted therapy.

WIPI1 is a conserved mediator of right ventricular failure

Right ventricular dysfunction is highly prevalent across cardiopulmonary diseases and independently predicts death in both heart failure (HF) and pulmonary hypertension (PH). Progression towards right ventricular failure (RVF) can occur in spite of optimal medical treatment of HF or PH, highlighting current insufficient understanding of RVF molecular pathophysiology. To identify molecular mechanisms that may distinctly underlie RVF, we investigated the cardiac ventricular transcriptome of advanced HF patients, with and without RVF. Using an integrated systems genomic and functional biology approach, we identified an RVF-specific gene module, for which WIPI1 served as a hub and HSPB6 and MAP4 as drivers, and confirmed the ventricular specificity of Wipi1, Hspb6, and Map4 transcriptional changes in adult murine models of pressure overload induced RV- versus LV- failure. We uncovered a shift towards non-canonical autophagy in the failing RV that correlated with RV-specific Wipi1 upregulation. In vitro siRNA silencing of Wipi1 in neonatal rat ventricular myocytes limited non-canonical autophagy and blunted aldosterone-induced mitochondrial superoxide levels. Our findings suggest that Wipi1 regulates mitochondrial oxidative signaling and non-canonical autophagy in cardiac myocytes. Together with our human transcriptomic analysis and corroborating studies in an RVF mouse model, these data render Wipi1 a potential target for RV-directed HF therapy.

Abstract 372: Master Transcriptional Regulators of Cardiac Gene Expression in Heart Failure

Background: Heart failure (HF) is characterized by complex transcriptional networks that direct the heart from a healthy to diseased state. Although some contributing genes have been identified through molecular biology and GWAS, heritability studies suggest that many genes have resisted discovery through these approaches. Identifying connective regulatory loci, especially master transcriptional regulators that affect the expression of many genes, offers a promising means of discovering novel relevant genes that have not been detected with other methods.

Methods and Results: Transcriptional regulators of HF were identified using nine-week-old female mice from 93 lines of the Hybrid Mouse Diversity Panel. Mice received 30 ug/g/day of isoproterenol (ISO) for 3 weeks to induce cardiac dysfunction. Transcriptomes were generated from left ventricles of these mice along with age-matched controls. Expression Quantitative Trait Loci (eQTLs) for 13,156 transcripts were identified using a mixed model in three conditions (control, treated, delta). Suggestive (P<1E-4) eQTLs were sorted into 500kb bins tiled across the genome to identify loci that regulate a significant number of transcripts. Ten hotspot loci that regulate over 5% (658 of 13156) of expressed genes were identified, several of which contain genes with known roles in HF, including Drosha , Akap5 and Dicer1 . Several novel regulators were also identified, including the Serine Proteinase Inhibitor, Serpina3n , which resides in a locus that regulates the change in expression of 9.7% (1276 of 13156) of all genes and is strongly correlated with changes in heart weight after ISO treatment. In subsequent in vitro work, Serpina3n knockdown resulted in reduced cellular hypertrophy, changes to hypertrophy-related gene expression, and modulation of the expression of several genes linked to its locus.

Conclusion: GWAS performed on over 20,000 transcripts in control and ISO-treated hearts identified 10 genomic loci that regulate over 5% of the expressed genes in the heart. Serpina3n is a novel master regulator of HF. Further analysis of other master regulatory loci will reveal additional genes and improve our understanding of the transcriptional networks that direct the progression towards heart failure.

Abstract 263: Cytosolic RBFox1 in Cardiac Pathological Remodeling

Background: RBFox1 is known to be an RNA splicing regulator with enriched expression in cardiac muscle. Loss of RBFox1 expression is a molecular hallmark associated with heart failure in mouse and human. Genetic manipulation of RBFox1 reveals a major function of RBFox1 in the pathogenesis of cardiac hypertrophy, fibrosis and dysfunction under pathological stresses. However, much of our current knowledge about RBFox1 focuses on the nuclear RBFox1 with a major impact on global alternative splicing changes. Yet, RBFox1 gene also generates a cytosolic isoform-RBFox1c through alternative splicing, and the specific function of RBFox1c has not been characterized.

Goal and Methods: This study investigated the functional impact and the underlying mechanism of the RBFox1c in cardiac pathological remodeling and targeted gene regulation.

Results: RBFox1c expression is significantly repressed in stressed cardiomyocytes in vivo and in vitro. RNA-Seq combined with IPA analyses from cardiomyocytes revealed RBFox1c but not the nucleus RBFox1 specifically suppressed pro-inflammatory genes. In the cardiac specific RBFox1 knockout mice, enhanced cardiac fibrosis is observed following I/R injury associated with elevated expression of pro-inflammatory genes. In contrast, cardiac specific expression of RBFox1c reduced cardiac fibrosis and inflammatory gene expression following pressure-overload and myocardial infarct injury associated with improved ejection fraction. Motif enrichment analysis identified significant enrichment of the RBFox1 binding motif in the 3’UTR of the RBFox1c regulated genes. We performed CLIP analysis followed by RT-PCR and observed RBFox1c interacted with inflammatory gene 3’UTR. Lastly, we explored the interactome of RBFox1c and found RBFox1c specifically interacted with a component of RNA decay machinery-Upf1. Indeed, while expression of RBFox1c repressed inflammatory gene expression, inactivation of Upf1 abolished this effect in cardiomyocytes.

Conclusion: RBFox1 regulates cardiac transcriptome reprogramming at two post-transcriptional steps. The RBFox1 nuclei isoform regulates RNA splicing reprogramming, and the RBFox1c represses proinflammatory genes via recruitment of Upf1 mediated RNA degradation.

Isoproterenol-Induced Heart Failure Mouse Model Using Osmotic Pump Implantation

Isoproterenol is used widely for inducing heart failure in mice. Isoproterenol is a nonselective beta-adrenergic agonist. The acute model mimics stress-induced cardiomyopathy. The chronic model mimics advanced heart failure in humans. In this chapter, we describe a protocol that we used to induce heart failure in 100+ strains of inbred mice. Techniques on surgical pump implantation and echocardiography are described in detail. We also discuss the impact of drug dosage, duration, mortality, age, gender, and strain on cardiac remodeling responses. The success of model creation may be assessed by echocardiogram or molecular markers. This chapter may be relevant to those who are interested in using this heart failure model.

Frequency of mononuclear diploid cardiomyocytes underlies natural variation in heart regeneration

Adult mammalian cardiomyocyte regeneration after injury is thought to be minimal. Mononuclear diploid cardiomyocytes (MNDCMs), a relatively small subpopulation in the adult heart, may account for the observed degree of regeneration, but this has not been tested. We surveyed 120 inbred mouse strains and found that the frequency of adult mononuclear cardiomyocytes was surprisingly variable (>7-fold). Cardiomyocyte proliferation and heart functional recovery after coronary artery ligation both correlated with pre-injury MNDCM content. Using genome-wide association, we identified Tnni3k as one gene that influences variation in this composition and demonstrated that Tnni3k knockout resulted in elevated MNDCM content and increased cardiomyocyte proliferation after injury. Reciprocally, overexpression of Tnni3k in zebrafish promoted cardiomyocyte polyploidization and compromised heart regeneration. Our results corroborate the relevance of MNDCMs in heart regeneration. Moreover, they imply that intrinsic heart regeneration is not limited nor uniform in all individuals, but rather is a variable trait influenced by multiple genes.

Abstract 324: Identification of Regulators of Cardiac DNA Methylation Using a Systems Genetics Approach in Mice

Systems biology approaches to studying heart failure in humans are hampered by numerous environmental factors and inciting incidents which combine to complicate the application of standard population-based tools and algorithms to the syndrome. We recently reported a study of heart failure in a large cohort of inbred mouse strains (the Hybrid Mouse Diversity Panel; HMDP) treated with the beta-adrenergic agonist isoproterenol. We demonstrated that it was possible to combine systems-level tools with the benefits of an animal model to capture and identify numerous genetic variations which drive heart failure.

Recent research on the epigenome has identified changes to DNA methylation which affect the progression of cardiovascular diseases and suggests that DNA methylation may serve as an important additional marker or even driver of genes involved in heart failure-associated phenotypes. We have supplemented our prior study by completing reduced representational bisulfite sequencing on 88 strains from our panel both with and without catecholamine challenge.

We have identified 75,000 CpGs which vary among the strains of the HMDP across the genome. Each CpG was mapped to the genome using GWAS to identify methylation quantitative trait loci (mQTLs). These mQTLs were then grouped together to identify mQTL hotspots, regions on the genome which regulate a sizable fractions of all observed CpGs. We then overlapped these hotspots with hotspots which regulate the expression of gene transcripts.

Three genomic regions were identified as multi-omic master regulators which affect both DNA methylation and gene expression for over 5% of the expressed transcripts and varying CpGs. Closer examination of these loci identified the serine peptidase inhibitor Serpina3n as a likely candidate gene for the regulation of DNA methylation, gene expression and cardiac phenotypes. Subsequent in vitro and in vivo work demonstrate that Serpina3n knockdown results in reduced cellular hypertrophy and changes to hypertrophy-related gene expression. Further analysis of the other master regulatory regions will likely reveal additional genes which will improve our understanding of how DNA methylation acts to regulate pathways underlying heart failure.

A systems genetics approach identifies Trp53inp2 as a link between cardiomyocyte glucose utilization and hypertrophic response

Cardiac failure has been widely associated with an increase in glucose utilization. The aim of our study was to identify factors that mechanistically bridge this link between hyperglycemia and heart failure. Here, we screened the Hybrid Mouse Diversity Panel (HMDP) for substrate-specific cardiomyocyte candidates based on heart transcriptional profile and circulating nutrients. Next, we utilized an in vitro model of rat cardiomyocytes to demonstrate that the gene expression changes were in direct response to substrate abundance. After overlaying candidates of interest with a separate HMDP study evaluating isoproterenol-induced heart failure, we chose to focus on the gene Trp53inp2 as a cardiomyocyte glucose utilization-specific factor. Trp53inp2 gene knockdown in rat cardiomyocytes reduced expression and protein abundance of key glycolytic enzymes. This resulted in reduction of both glucose uptake and glycogen content in cardiomyocytes stimulated with isoproterenol. Furthermore, this reduction effectively blunted the capacity of glucose and isoprotereonol to synergistically induce hypertrophic gene expression and cell size expansion. We conclude that Trp53inp2 serves as regulator of cardiomyocyte glycolytic activity and can consequently regulate hypertrophic response in the context of elevated glucose content.NEW & NOTEWORTHY Here, we apply a novel method for screening transcripts based on a substrate-specific expression pattern to identify Trp53inp2 as an induced cardiomyocyte glucose utilization factor. We further show that reducing expression of the gene could effectively blunt hypertrophic response in the context of elevated glucose content.

Systems Genetics Approach Identifies Gene Pathways and Adamts2 as Drivers of Isoproterenol-Induced Cardiac Hypertrophy and Cardiomyopathy in Mice

We previously reported a genetic analysis of heart failure traits in a population of inbred mouse strains treated with isoproterenol to mimic catecholamine-driven cardiac hypertrophy. Here, we apply a co-expression network algorithm, wMICA, to perform a systems-level analysis of left ventricular transcriptomes from these mice. We describe the features of the overall network but focus on a module identified in treated hearts that is strongly related to cardiac hypertrophy and pathological remodeling. Using the causal modeling algorithm NEO, we identified the gene Adamts2 as a putative regulator of this module and validated the predictive value of NEO using small interfering RNA-mediated knockdown in neonatal rat ventricular myocytes. Adamts2 silencing regulated the expression of the genes residing within the module and impaired isoproterenol-induced cellular hypertrophy. Our results provide a view of higher order interactions in heart failure with potential for diagnostic and therapeutic insights.

A Suite of Tools for Biologists That Improve Accessibility and Visualization of Large Systems Genetics Datasets: Applications to the Hybrid Mouse Diversity Panel

In this chapter we address the recent explosion in large multilevel population studies such as the METSIM study in humans as well as large panels of animal models such as the Hybrid Mouse Diversity Panel or the BXD set of recombinant inbred strains. These studies have harnessed the increasing affordability of large-scale high-throughput profiling to gather massive quantities of data. These datasets, spread across different -omics levels (genome, transcriptome, etc.), different tissues (e.g. heart, plasma, bone) and different environmental factors (e.g. diet, drugs) each individually have led to a number of novel findings relevant to a variety of complex diseases and other phenotypes. The analysis of these results, however, is often limited to individuals with a comprehensive understanding of database languages such as SQL. In this chapter, we describe the development of a GUI-based database analysis suite, using the Hybrid Mouse Diversity Panel as an example to lay out a series of methods for visualization and integration of large systems genetics datasets. The database is based on the Shiny suite of tools in R, and is transferrable to other SQL-based datasets.

Deconvolution of the Human Endothelial Transcriptome

A systems approach deconvolutes genes specific to and enriched in endothelium from whole-organ transcriptome data, with applications to other cell types and tissues.

Abstract 133: A Systems Genetics Approach to Identify Genetic Pathways and Key Drivers of Isoproterenol-induced Cardiac Hypertrophy and Cardiomyopathy in Mice

Heart Failure (HF) is a complex disease involving numerous environmental and genetic factors. We previously reported a genetic analysis of HF traits in a population of inbred mouse strains treated with isoproterenol, a β-adrenergic agonist used to mimic catecholamine-driven cardiac hypertrophy. We now present a systems genetics analysis in which we have used left ventricular transcript levels from these mice to perform co-expression network modeling. We constructed gene networks composed of 8,126 genes and 20 modules using the wMICA algorithm. In the wMICA network generated from treated hearts, we identified a module with significant correlations to several HF-related phenotypic traits. Further analysis of this module showed significant over-representation of genes known to contribute to the development of HF. Using the causal modeling algorithm NEO, we identified the gene Adamts2 as a putative master regulator of the module. We then validated the role of this gene through siRNA-mediated knockdown in neonatal rat ventricular myocytes (NRVM). Consistent with our model, Adamts2 silencing was able to regulate the expression of the genes residing within the module as well as impairing isoproterenol-induced cell size changes . Our results provide a view of higher order interactions in heart failure with potential to facilitate diagnostic and therapeutic approaches.

Relationship of disease-associated gene expression to cardiac phenotype is buffered by genetic diversity and chromatin regulation

Expression of a cohort of disease-associated genes, some of which are active in fetal myocardium, is considered a hallmark of transcriptional change in cardiac hypertrophy models. How this transcriptome remodeling is affected by the common genetic variation present in populations is unknown. We examined the role of genetics, as well as contributions of chromatin proteins, to regulate cardiac gene expression and heart failure susceptibility. We examined gene expression in 84 genetically distinct inbred strains of control and isoproterenol-treated mice, which exhibited varying degrees of disease. Unexpectedly, fetal gene expression was not correlated with hypertrophic phenotypes. Unbiased modeling identified 74 predictors of heart mass after isoproterenol-induced stress, but these predictors did not enrich for any cardiac pathways. However, expanded analysis of fetal genes and chromatin remodelers as groups correlated significantly with individual systemic phenotypes. Yet, cardiac transcription factors and genes shown by gain-/loss-of-function studies to contribute to hypertrophic signaling did not correlate with cardiac mass or function in disease. Because the relationship between gene expression and phenotype was strain specific, we examined genetic contribution to expression. Strikingly, strains with similar transcriptomes in the basal heart did not cluster together in the isoproterenol state, providing comprehensive evidence that there are different genetic contributors to physiological and pathological gene expression. Furthermore, the divergence in transcriptome similarity versus genetic similarity between strains is organ specific and genome-wide, suggesting chromatin is a critical buffer between genetics and gene expression.

Reciprocal Regulation of the Cardiac Epigenome by Chromatin Structural Proteins Hmgb and Ctcf: IMPLICATIONS FOR TRANSCRIPTIONAL REGULATION

Transcriptome remodeling in heart disease occurs through the coordinated actions of transcription factors, histone modifications, and other chromatin features at pathology-associated genes. The extent to which genome-wide chromatin reorganization also contributes to the resultant changes in gene expression remains unknown. We examined the roles of two chromatin structural proteins, Ctcf (CCCTC-binding factor) and Hmgb2 (high mobility group protein B2), in regulating pathologic transcription and chromatin remodeling. Our data demonstrate a reciprocal relationship between Hmgb2 and Ctcf in controlling aspects of chromatin structure and gene expression. Both proteins regulate each others' expression as well as transcription in cardiac myocytes; however, only Hmgb2 does so in a manner that involves global reprogramming of chromatin accessibility. We demonstrate that the actions of Hmgb2 on local chromatin accessibility are conserved across genomic loci, whereas the effects on transcription are loci-dependent and emerge in concert with histone modification and other chromatin features. Finally, although both proteins share gene targets, Hmgb2 and Ctcf, neither binds these genes simultaneously nor do they physically colocalize in myocyte nuclei. Our study uncovers a previously unknown relationship between these two ubiquitous chromatin proteins and provides a mechanistic explanation for how Hmgb2 regulates gene expression and cellular phenotype. Furthermore, we provide direct evidence for structural remodeling of chromatin on a genome-wide scale in the setting of cardiac disease.

The Hybrid Mouse Diversity Panel: a resource for systems genetics analyses of metabolic and cardiovascular traits

The Hybrid Mouse Diversity Panel (HMDP) is a collection of approximately 100 well-characterized inbred strains of mice that can be used to analyze the genetic and environmental factors underlying complex traits. While not nearly as powerful for mapping genetic loci contributing to the traits as human genome-wide association studies, it has some important advantages. First, environmental factors can be controlled. Second, relevant tissues are accessible for global molecular phenotyping. Finally, because inbred strains are renewable, results from separate studies can be integrated. Thus far, the HMDP has been studied for traits relevant to obesity, diabetes, atherosclerosis, osteoporosis, heart failure, immune regulation, fatty liver disease, and host-gut microbiota interactions. High-throughput technologies have been used to examine the genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes of the mice under various environmental conditions. All of the published data are available and can be readily used to formulate hypotheses about genes, pathways and interactions.

Catabolic Defect of Branched-Chain Amino Acids Promotes Heart Failure

BACKGROUND

Although metabolic reprogramming is critical in the pathogenesis of heart failure, studies to date have focused principally on fatty acid and glucose metabolism. Contribution of amino acid metabolic regulation in the disease remains understudied.

METHODS AND RESULTS

Transcriptomic and metabolomic analyses were performed in mouse failing heart induced by pressure overload. Suppression of branched-chain amino acid (BCAA) catabolic gene expression along with concomitant tissue accumulation of branched-chain α-keto acids was identified as a significant signature of metabolic reprogramming in mouse failing hearts and validated to be shared in human cardiomyopathy hearts. Molecular and genetic evidence identified the transcription factor Krüppel-like factor 15 as a key upstream regulator of the BCAA catabolic regulation in the heart. Studies using a genetic mouse model revealed that BCAA catabolic defect promoted heart failure associated with induced oxidative stress and metabolic disturbance in response to mechanical overload. Mechanistically, elevated branched-chain α-keto acids directly suppressed respiration and induced superoxide production in isolated mitochondria. Finally, pharmacological enhancement of branched-chain α-keto acid dehydrogenase activity significantly blunted cardiac dysfunction after pressure overload.

CONCLUSIONS

BCAA catabolic defect is a metabolic hallmark of failing heart resulting from Krüppel-like factor 15-mediated transcriptional reprogramming. BCAA catabolic defect imposes a previously unappreciated significant contribution to heart failure.

DNA Methylation Indicates Susceptibility to Isoproterenol-Induced Cardiac Pathology and Is Associated With Chromatin States

RATIONALE

Only a small portion of the known heritability of cardiovascular diseases, such as heart failure, can be explained based on single-gene mutations. Chromatin structure and regulation provide a substrate through which genetic differences in noncoding regions may affect cellular function and response to disease, but the mechanisms are unknown.

OBJECTIVE

We conducted genome-wide measurements of DNA methylation in different strains of mice that are susceptible and resistant to isoproterenol-induced dysfunction to test the hypothesis that this epigenetic mark may play a causal role in the development of heart failure.

METHODS AND RESULTS

BALB/cJ and BUB/BnJ mice, determined to be susceptible and resistant to isoproterenol-induced heart failure, respectively, were administered the drug for 3 weeks via osmotic minipump. Reduced representational bisulfite sequencing was then used to compare the differences between the cardiac DNA methylomes in the basal state between strains and then after isoproterenol treatment. Single-base resolution DNA methylation measurements were obtained and revealed a bimodal distribution of methylation in the heart, enriched in lone intergenic CpGs and depleted from CpG islands around genes. Isoproterenol induced global decreases in methylation in both strains; however, the basal methylation pattern between strains shows striking differences that may be predictive of disease progression before environmental stress. The global correlation between promoter methylation and gene expression (as measured by microarray) was modest and revealed itself only with focused analyses of transcription start site and gene body regions (in contrast to when gene methylation was examined in toto). Modules of comethylated genes displayed correlation with other protein-based epigenetic marks, supporting the hypothesis that chromatin modifications act in a combinatorial manner to specify transcriptional phenotypes in the heart.

CONCLUSIONS

This study provides the first single-base resolution map of the mammalian cardiac DNA methylome and the first case-control analysis of the changes in DNA methylation with heart failure. The findings demonstrate marked genetic differences in DNA methylation that are associated with disease progression.

RBFox1-mediated RNA splicing regulates cardiac hypertrophy and heart failure

RNA splicing is a major contributor to total transcriptome complexity; however, the functional role and regulation of splicing in heart failure remain poorly understood. Here, we used a total transcriptome profiling and bioinformatic analysis approach and identified a muscle-specific isoform of an RNA splicing regulator, RBFox1 (also known as A2BP1), as a prominent regulator of alternative RNA splicing during heart failure. Evaluation of developing murine and zebrafish hearts revealed that RBFox1 is induced during postnatal cardiac maturation. However, we found that RBFox1 is markedly diminished in failing human and mouse hearts. In a mouse model, RBFox1 deficiency in the heart promoted pressure overload-induced heart failure. We determined that RBFox1 is a potent regulator of RNA splicing and is required for a conserved splicing process of transcription factor MEF2 family members that yields different MEF2 isoforms with differential effects on cardiac hypertrophic gene expression. Finally, induction of RBFox1 expression in murine pressure overload models substantially attenuated cardiac hypertrophy and pathological manifestations. Together, this study identifies regulation of RNA splicing by RBFox1 as an important player in transcriptome reprogramming during heart failure that influence pathogenesis of the disease.

Abstract 128: Network-based Approaches to Identify Novel Regulators of Heart Failure

Heart failure is a highly heterogeneous disorder characterized by the interactions of multiple environmental and genetic factors. While reductionistic approaches have made significant inroads into characterizing the pathophysiology of the syndrome, they are unable to properly dissect the complex interactions between sets of genes and pathways which result in the emergent phenotypes . Systems genetics offers a means by which these interactions may be identified and explored. We have developed a resource, the Hybrid Mouse Diversity Panel (HMDP) to perform systems-level analyses in mice. Nine week old female mice from 93 unique inbred lines of the HMDP were give 30 ug/g/day of isoproterenol through an abdominally implanted Alzet micropump. After three weeks, mice were sacrificed along with age-matched controls. A portion of the left ventricle was arrayed on an Illumina Mouse Ref 8.0 platform.

Maximal Information Component Analysis was used to construct gene networks, and a module of 41 genes was identified which shows strong correlation to a number of important phenotypic traits, including heart weight and cardiac fibrosis. This module contains a number of genes of interest, including Lgals3, a diagnostic marker for heart failure. Through the use of structural equation modeling, we identified several key genes within the module for further analysis, the most important of which is the metalloprotease Adamts2.

We have performed a series of in vitro analyses demonstrating the important role of Adamts2 in this module using neonatal rat ventricular myocytes. Knockout of Adamts2 results in an amelioration of the hypertrophic response to catecholamine stimulation as well as a reduction of hypertrophic markers such as Nppa and Nppb. Furthermore, we observe that other genes in the module no longer respond to catecholamine stimulation after knockdown of Adamts2.

Genetic architecture of insulin resistance in the mouse

Insulin resistance (IR) is a complex trait with multiple genetic and environmental components. Confounded by large differences between the sexes, environment, and disease pathology, the genetic basis of IR has been difficult to dissect. Here we examine IR and related traits in a diverse population of more than 100 unique male and female inbred mouse strains after feeding a diet rich in fat and refined carbohydrates. Our results show dramatic variation in IR among strains of mice and widespread differences between sexes that are dependent on genotype. We uncover more than 15 genome-wide significant loci and validate a gene, Agpat5, associated with IR. We also integrate plasma metabolite levels and global gene expression from liver and adipose tissue to identify metabolite quantitative trait loci (mQTL) and expression QTL (eQTL), respectively. Our results provide a resource for analysis of interactions between diet, sex, and genetic background in IR.

Mapping genetic contributions to cardiac pathology induced by Beta-adrenergic stimulation in mice

BACKGROUND

Chronic stress-induced cardiac pathology exhibits both a wide range in severity and a high degree of heterogeneity in clinical manifestation in human patients. This variability is contributed to by complex genetic and environmental etiologies within the human population. Genetic approaches to elucidate the genetics underlying the acquired forms of cardiomyopathies, including genome-wide association studies, have been largely unsuccessful, resulting in limited knowledge as to the contribution of genetic variations for this important disease.

METHODS AND RESULTS

Using the β-adrenergic agonist isoproterenol as a specific pathological stressor to circumvent the problem of etiologic heterogeneity, we performed a genome-wide association study for genes influencing cardiac hypertrophy and fibrosis in a large panel of inbred mice. Our analyses revealed 7 significant loci and 17 suggestive loci, containing an average of 14 genes, affecting cardiac hypertrophy, fibrosis, and surrogate traits relevant to heart failure. Several loci contained candidate genes which are known to contribute to Mendelian cardiomyopathies in humans or have established roles in cardiac pathology based on molecular or genetic studies in mouse models. In particular, we identify Abcc6 as a novel gene underlying a fibrosis locus by validating that an allele with a splice mutation of Abcc6 dramatically and rapidly promotes isoproterenol-induced cardiac fibrosis.

CONCLUSIONS

Genetic variants significantly contribute to the phenotypic heterogeneity of stress-induced cardiomyopathy. Systems genetics is an effective approach to identify genes and pathways underlying the specific pathological features of cardiomyopathies. Abcc6 is a previously unrecognized player in the development of stress-induced cardiac fibrosis.

Abstract 163: Genetic Basis of Isoproterenol-Induced Cardiac Fibrosis

Background: Cardiac fibrosis is a common pathology in the diseased heart, which can cause a loss of elasticity and contractile dysfunction. Cardiac fibrosis is a complex process driven by many pathological triggers which involve numerous genes, pathways and cell types. Despite its importance, the genetic basis for the development of cardiac fibrosis has not been systematically explored.

Methods and Results: We have developed a resource, the Hybrid Mouse Diversity Panel (HMDP) for high resolution GWAS and systems genetics study of quantitative traits in mice. Eight week old female mice from 80 unique inbred strains of the HMDP were given 30 ug/g/day of isoproterenol (ISO) for three weeks and cardiac fibrosis was assessed by Masson Trichrome staining which revealed a wide spectrum in the degree of fibrosis among the HMDP strains both before and after treatment. Using the Efficient Mixed Model Algorithm, we identified 13 significant or suggestive loci contributing to cardiac fibrosis, many containing numerous gene candidates. Within one of these loci, Abcc6, an orphan ABC transporter linked to the human disease pseudoxanthoma elasticum, was identified as a possible candidate for ISO-induced cardiac fibrosis. A splice-site mutation present in 19 strains of the HMDP was significantly linked to a higher degree of ISO-induced cardiac fibrosis(P=1E-4) but was not linked to increased fibrosis in untreated animals(P=0.25). Targeted genetic knockout of Abcc6 promoted ISO-induced cardiac fibrosis while reintroducing the wildtype Abcc6 allele to an genetic strain homozygous for the Abcc6 splice site mutation significantly alleviated ISO-induced cardiac fibrosis.

Conclusion: A GWAS performed on levels of cardiac fibrosis observed in ISO treated animals using HMDP mice as model system uncovered significant genetic contributions to stress-induced cardiac fibrosis. Abcc6 is a novel gene contributing to ISO-induced cardiac fibrosis in the heart.

Abstract 346: Genome-wide Bisulfite Sequencing After Isoproterenol Identifies DNA Methylation Modules Influencing Heart Failure Susceptibility

DNA methylation is an epigenetic mechanism that controls gene expression. Recent studies of human samples linked dysregulation of DNA methylation to cardiovascular diseases. However, whether DNA methylation is mechanistically involved in disease pathogenesis is unknown. To determine how DNA methylation participates in the development of heart failure, we measured the DNA methylome in healthy and hypertrophic mouse hearts (and in isolated cardiac myocytes in parallel experiments) using reduced representational bisulfite sequencing. Isoproterenol (ISO) minipumps were implanted in two mouse strains with opposite phenotypes: BUB/BnJ, which is resistant to ISO-induced hypertrophy/failure, and BALB/cJ, which is susceptible. DNA and mRNA were isolated from hearts and myocytes and analyzed by bisulfite sequencing and microarrays, respectively. The results reveal three levels of information about the methylome: basal differences between the resistant and susceptible strains, loci affected in a disease-associated manner, and strain-specific changes in methylation following ISO treatment_which serve as novel targets to understand the genetic basis of differential incidence of heart failure. We observed 1,122 loci undergoing a >20% change in methylation after ISO in either strain (p<0.05). Our data also showed significant ISO-induced methylation differences in genes related to myofibril assembly (GO:0031032, p=6e-7) and increased heart weight (MP:0002833, p=2e-6). We selected the top 15,000 promoter-associated CpGs with high variation among samples and carried out an unbiased weighted correlation network analysis (WGCNA) of these methylation data. We identified a module of promoter-associated CpGs whose demethylation is highly correlated with ISO treatment in both strains (75 CpGs, Pearson correlation=0.898, p=0.001). We also identified modules with strain-specific responses to ISO treatment. Interestingly, we found a module of 109 CpGs whose methylation is increased in BALB/cJ strain after ISO treatment, but decreased in BUB/BnJ strain. Our data demonstrate global changes in DNA methylation in the adult heart during the development of disease and reveal networks of modified loci that influence heart failure susceptibility.

Abstract 233: Isoproterenol-induced Cardiac Hypertrophy And Failure In Mice: Gene Network Modeling

Heart failure is highly heterogeneous and as a result, relatively few insights into the pathways and drivers of heart failure have been identified using system-wide methods such as genome-wide association studies (GWAS). We have developed a resource, the Hybrid Mouse Diversity Panel (HMDP) for high resolution GWAS and systems genetics in mice. Eight week old female mice from 93 unique inbred strains of the HMDP were given 20 μg/g/day of isoproterenol through an abdominally implanted Alzet micropump. Three weeks post-implantation, all mice were sacrificed, along with age-matched controls. The mice exhibited widely varying degrees of hypertrophy and heart functioning. A portion of the left ventricle was processed and arrayed on an Illumina Mouse Ref 8.0 platform.

We used Maximal Information Component Analysis, a novel method of network construction which allows for non-linear relationships between genes as well as non-binary partitioning of genes into sub-networks to subdivide the expression data into a series of modules. In order to identify modules which may contribute to Isoproterenol-induced hypertrophy and failure, we examined the correlation of each module to clinically relevant cardiac traits traits such as organ weights and echocardiographic parameters.

We identified several modules with strong correlations to multiple heart failure-related clinical traits, including one module of 41 genes which contained several genes of interest, including Lgals3, a diagnostic marker for heart failure. Utilizing eQTL hotspot analysis, we have identified a locus which is involved in the regulation of this module. A gene within this locus, Magi2, regulates the turnover of the β-adrenergic receptor and represents a likely candidate for the response to isoproterenol.

Maximal information component analysis: a novel non-linear network analysis method

Background: Network construction and analysis algorithms provide scientists with the ability to sift through high-throughput biological outputs, such as transcription microarrays, for small groups of genes (modules) that are relevant for further research. Most of these algorithms ignore the important role of non-linear interactions in the data, and the ability for genes to operate in multiple functional groups at once, despite clear evidence for both of these phenomena in observed biological systems.

Results: We have created a novel co-expression network analysis algorithm that incorporates both of these principles by combining the information-theoretic association measure of the maximal information coefficient (MIC) with an Interaction Component Model. We evaluate the performance of this approach on two datasets collected from a large panel of mice, one from macrophages and the other from liver by comparing the two measures based on a measure of module entropy, Gene Ontology (GO) enrichment, and scale-free topology (SFT) fit. Our algorithm outperforms a widely used co-expression analysis method, weighted gene co-expression network analysis (WGCNA), in the macrophage data, while returning comparable results in the liver dataset when using these criteria. We demonstrate that the macrophage data has more non-linear interactions than the liver dataset, which may explain the increased performance of our method, termed Maximal Information Component Analysis (MICA) in that case.

Conclusions: In making our network algorithm more accurately reflect known biological principles, we are able to generate modules with improved relevance, particularly in networks with confounding factors such as gene by environment interactions.

Genome-wide association mapping of blood cell traits in mice

Genetic variations in blood cell parameters can impact clinical traits. We report here the mapping of blood cell traits in a panel of 100 inbred strains of mice of the Hybrid Mouse Diversity Panel (HMDP) using genome-wide association (GWA). We replicated a locus previously identified in using linkage analysis in several genetic crosses for mean corpuscular volume (MCV) and a number of other red blood cell traits on distal chromosome 7. Our peak for SNP association to MCV occurred in a linkage disequilibrium (LD) block spanning from 109.38 to 111.75 Mb that includes Hbb-b1, the likely causal gene. Altogether, we identified five loci controlling red blood cell traits (on chromosomes 1, 7, 11, 12, and 16), and four of these correspond to loci for red blood cell traits reported in a recent human GWA study. For white blood cells, including granulocytes, monocytes, and lymphocytes, a total of six significant loci were identified on chromosomes 1, 6, 8, 11, 12, and 15. An average of ten candidate genes were found at each locus and those were prioritized by examining functional variants in the HMDP such as missense and expression variants. These results provide intermediate phenotypes and candidate loci for genetic studies of atherosclerosis and cancer as well as inflammatory and immune disorders in mice.

Genetic control of obesity and gut microbiota composition in response to high-fat, high-sucrose diet in mice

Obesity is a highly heritable disease driven by complex interactions between genetic and environmental factors. Human genome-wide association studies (GWAS) have identified a number of loci contributing to obesity; however, a major limitation of these studies is the inability to assess environmental interactions common to obesity. Using a systems genetics approach, we measured obesity traits, global gene expression, and gut microbiota composition in response to a high-fat/high-sucrose (HF/HS) diet of more than 100 inbred strains of mice. Here we show that HF/HS feeding promotes robust, strain-specific changes in obesity that are not accounted for by food intake and provide evidence for a genetically determined set point for obesity. GWAS analysis identified 11 genome-wide significant loci associated with obesity traits, several of which overlap with loci identified in human studies. We also show strong relationships between genotype and gut microbiota plasticity during HF/HS feeding and identify gut microbial phylotypes associated with obesity.

"Good enough solutions" and the genetics of complex diseases

In this Emerging Science Review, we discuss a systems genetics strategy, which we call gene module association study (GMAS), as a novel approach complementing genome-wide association studies (GWAS), to understand complex diseases by focusing on how genes work together in groups rather than singly. The first step is to characterize phenotypic differences among a genetically diverse population. The second step is to use gene expression microarray (or other high-throughput) data from the population to construct gene coexpression networks. Coexpression analysis typically groups 20 000 genes into 20 to 30 modules containing tens to hundreds of genes, whose aggregate behavior can be represented by the module's "eigengene." The third step is to correlate expression patterns with phenotype, as in GWAS, only applied to eigengenes instead of single nucleotide polymorphisms. The goal of the GMAS approach is to identify groups of coregulated genes that explain complex traits from a systems perspective. From an evolutionary standpoint, we hypothesize that variability in eigengene patterns reflects the "good enough solution" concept, that biological systems are sufficiently complex so that many possible combinations of the same elements (in this case eigengenes) can produce an equivalent output, that is, a "good enough solution" to accomplish normal biological functions. However, when faced with environmental stresses, some "good enough solutions" adapt better than others, explaining individual variability to disease and drug susceptibility. If validated, GMAS may imply that common polygenic diseases are related as much to group interactions between normal genes, as to multiple gene mutations.

Hybrid mouse diversity panel: a panel of inbred mouse strains suitable for analysis of complex genetic traits

We have developed an association-based approach using classical inbred strains of mice in which we correct for population structure, which is very extensive in mice, using an efficient mixed-model algorithm. Our approach includes inbred parental strains as well as recombinant inbred strains in order to capture loci with effect sizes typical of complex traits in mice (in the range of 5% of total trait variance). Over the last few years, we have typed the hybrid mouse diversity panel (HMDP) strains for a variety of clinical traits as well as intermediate phenotypes and have shown that the HMDP has sufficient power to map genes for highly complex traits with resolution that is in most cases less than a megabase. In this essay, we review our experience with the HMDP, describe various ongoing projects, and discuss how the HMDP may fit into the larger picture of common diseases and different approaches.

Abstract 16: Genomewide Association Study of Isoproterenol-Induced Heart Failure in a Large Mouse Panel

Heart failure is highly heterogeneous and association studies in humans have yielded few insights into its genetic basis. We have developed a resource, the Hybrid Mouse Diversity Panel, to efficiently perform association studies on complex diseases in a mouse model. Each strain within the panel has been densely genotyped and the panel displays significant baseline inter-strain variation. We used the panel to explore isoproterenol (a β-adrenergic agonist) induced heart failure.

Eight week old females from 105 unique inbred strains (average N = 6.7) were divided into control (average N = 2.5) and treated (average N = 4.1) cohorts. Treated mice received 20 μg/g/day of drug through an abdominally implanted Alzet micropump. All mice underwent echocardiography to assess left ventricular function both before and at weekly timepoints after treatment. At three weeks, all mice were sacrificed. Hearts (sectioned by chamber) lungs, liver and adrenal glands were weighed before storage for further analysis. Phenotypes were analyzed using the Efficient Mixed-Model Association (EMMA) algorithm to correct for population substructure. Promising gene candidates were tested on zebrafish morpholino models to assess any phenotypic effects.

Here we report initial findings from the panel. Chronic β-adrenergic stimulation results in marked variations in both weight and echocardiographic measurements. EMMA analysis of the data revealed several dozen putative peaks, including several repeated peaks in correlated phenotypes as well as replication of previously reported loci in both human and mouse studies. Further analysis of these peaks will shed light on the genetics underlying heart failure.