Common forms of atherosclerosis involve multiple genetic and environmental factors. While human genome-wide association studies have identified numerous loci contributing to coronary artery disease and its risk factors, these studies are unable to control environmental factors or examine detailed molecular traits in relevant tissues. We now report a study of natural variations contributing to atherosclerosis and related traits in over 100 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP). The mice were made hyperlipidemic by transgenic expression of human apolipoprotein E-Leiden (APOE-Leiden) and human cholesteryl ester transfer protein (CETP). The mice were examined for lesion size and morphology as well as plasma lipid, insulin and glucose levels, and blood cell profiles. A subset of mice was studied for plasma levels of metabolites and cytokines. We also measured global transcript levels in aorta and liver. Finally, the uptake of acetylated LDL by macrophages from HMDP mice was quantitatively examined. Loci contributing to the traits were mapped using association analysis, and relationships among traits were examined using correlation and statistical modeling. A number of conclusions emerged. First, relationships among atherosclerosis and the risk factors in mice resemble those found in humans. Second, a number of trait-loci were identified, including some overlapping with previous human and mouse studies. Third, gene expression data enabled enrichment analysis of pathways contributing to atherosclerosis and prioritization of candidate genes at associated loci in both mice and humans. Fourth, the data provided a number of mechanistic inferences; for example, we detected no association between macrophage uptake of acetylated LDL and atherosclerosis. Fifth, broad sense heritability for atherosclerosis was much larger than narrow sense heritability, indicating an important role for gene-by-gene interactions. Sixth, stepwise linear regression showed that the combined variations in plasma metabolites, including LDL/VLDL-cholesterol, trimethylamine N-oxide (TMAO), arginine, glucose and insulin, account for approximately 30 to 40% of the variation in atherosclerotic lesion area. Overall, our data provide a rich resource for studies of complex interactions underlying atherosclerosis.

The osteoblast-lineage consists of cells at various stages of maturation that are essential for skeletal development, growth, and maintenance. Over the past decade, many of the signaling cascades that regulate this lineage have been elucidated; however, little is known of the networks that coordinate, modulate, and transmit these signals. Here, we identify a gene network specific to the osteoblast-lineage through the reconstruction of a bone co-expression network using microarray profiles collected on 96 Hybrid Mouse Diversity Panel (HMDP) inbred strains. Of the 21 modules that comprised the bone network, module 9 (M9) contained genes that were highly correlated with prototypical osteoblast maker genes and were more highly expressed in osteoblasts relative to other bone cells. In addition, the M9 contained many of the key genes that define the osteoblast-lineage, which together suggested that it was specific to this lineage. To use the M9 to identify novel osteoblast genes and highlight its biological relevance, we knocked-down the expression of its two most connected "hub" genes, Maged1 and Pard6g. Their perturbation altered both osteoblast proliferation and differentiation. Furthermore, we demonstrated the mice deficient in Maged1 had decreased bone mineral density (BMD). It was also discovered that a local expression quantitative trait locus (eQTL) regulating the Wnt signaling antagonist Sfrp1 was a key driver of the M9. We also show that the M9 is associated with BMD in the HMDP and is enriched for genes implicated in the regulation of human BMD through genome-wide association studies. In conclusion, we have identified a physiologically relevant gene network and used it to discover novel genes and regulatory mechanisms involved in the function of osteoblast-lineage cells. Our results highlight the power of harnessing natural genetic variation to generate co-expression networks that can be used to gain insight into the function of specific cell-types.

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.

In the United States, roughly 10% of the population is exposed daily to hazardous levels of noise in the workplace. Twin studies estimate heritability for noise-induced hearing loss (NIHL) of approximately 36%, and strain specific variation in sensitivity has been demonstrated in mice. Based upon the difficulties inherent to the study of NIHL in humans, we have turned to the study of this complex trait in mice. We exposed 5 week-old mice from the Hybrid Mouse Diversity Panel (HMDP) to a 10 kHz octave band noise at 108 dB for 2 hours and assessed the permanent threshold shift 2 weeks post exposure using frequency specific stimuli. These data were then used in a genome-wide association study (GWAS) using the Efficient Mixed Model Analysis (EMMA) to control for population structure. In this manuscript we describe our GWAS, with an emphasis on a significant peak for susceptibility to NIHL on chromosome 17 within a haplotype block containing NADPH oxidase-3 (Nox3). Our peak was detected after an 8 kHz tone burst stimulus. Nox3 mutants and heterozygotes were then tested to validate our GWAS. The mutants and heterozygotes demonstrated a greater susceptibility to NIHL specifically at 8 kHz both on measures of distortion product otoacoustic emissions (DPOAE) and on auditory brainstem response (ABR). We demonstrate that this sensitivity resides within the synaptic ribbons of the cochlea in the mutant animals specifically at 8 kHz. Our work is the first GWAS for NIHL in mice and elucidates the power of our approach to identify tonotopic genetic susceptibility to NIHL.

The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography-Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications.

The integration of expression profiling with linkage analysis has increasingly been used to identify genes underlying complex phenotypes. The effects of gender on the regulation of many physiological traits are well documented; however, "genetical genomic" analyses have not yet addressed the degree to which their conclusions are affected by sex. We constructed and densely genotyped a large F2 intercross derived from the inbred mouse strains C57BL/6J and C3H/HeJ on an apolipoprotein E null (ApoE-/-) background. This BXH.ApoE-/- population recapitulates several "metabolic syndrome" phenotypes. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of linkage on sex. We detected several thousand liver gene expression quantitative trait loci, a significant proportion of which are sex-biased. We used these analyses to dissect the genetics of gonadal fat mass, a complex trait with sex-specific regulation. We present evidence for a remarkably high degree of sex-dependence on both the cis and trans regulation of gene expression. We demonstrate how these analyses can be applied to the study of the genetics underlying gonadal fat mass, a complex trait showing significantly female-biased heritability. These data have implications on the potential effects of sex on the genetic regulation of other complex traits.

We aimed to understand the genetic control of cardiac remodeling using an isoproterenol-induced heart failure model in mice, which allowed control of confounding factors in an experimental setting. We characterized the changes in cardiac structure and function in response to chronic isoproterenol infusion using echocardiography in a panel of 104 inbred mouse strains. We showed that cardiac structure and function, whether under normal or stress conditions, has a strong genetic component, with heritability estimates of left ventricular mass between 61% and 81%. Association analyses of cardiac remodeling traits, corrected for population structure, body size and heart rate, revealed 17 genome-wide significant loci, including several loci containing previously implicated genes. 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. Using this approach, we have validated a novel gene, Myh14, as a negative regulator of ISO-induced left ventricular mass hypertrophy in an in vivo mouse model and demonstrated the up-regulation of immediate early gene Myc, fetal gene Nppb, and fibrosis gene Lgals3 in ISO-treated Myh14 deficient hearts compared to controls.

Cardiovascular diseases (CVD) and type 2 diabetes (T2D) are closely interrelated complex diseases likely sharing overlapping pathogenesis driven by aberrant activities in gene networks. However, the molecular circuitries underlying the pathogenic commonalities remain poorly understood. We sought to identify the shared gene networks and their key intervening drivers for both CVD and T2D by conducting a comprehensive integrative analysis driven by five multi-ethnic genome-wide association studies (GWAS) for CVD and T2D, expression quantitative trait loci (eQTLs), ENCODE, and tissue-specific gene network models (both co-expression and graphical models) from CVD and T2D relevant tissues. We identified pathways regulating the metabolism of lipids, glucose, and branched-chain amino acids, along with those governing oxidation, extracellular matrix, immune response, and neuronal system as shared pathogenic processes for both diseases. Further, we uncovered 15 key drivers including HMGCR, CAV1, IGF1 and PCOLCE, whose network neighbors collectively account for approximately 35% of known GWAS hits for CVD and 22% for T2D. Finally, we cross-validated the regulatory role of the top key drivers using in vitro siRNA knockdown, in vivo gene knockout, and two Hybrid Mouse Diversity Panels each comprised of >100 strains. Findings from this in-depth assessment of genetic and functional data from multiple human cohorts provide strong support that common sets of tissue-specific molecular networks drive the pathogenesis of both CVD and T2D across ethnicities and help prioritize new therapeutic avenues for both CVD and T2D.

Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight-related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.

Antisense oligonucleotides (ASOs) have demonstrated variation of efficacy in patient populations. This has prompted our investigation into the contribution of genetic architecture to ASO pharmacokinetics (PK) and pharmacodynamics (PD). Genome wide association (GWA) and transcriptomic analysis in a hybrid mouse diversity panel (HMDP) were used to identify and validate novel genes involved in the uptake and efficacy of a single dose of a Malat1 constrained ethyl (cEt) modified ASO. The GWA of the HMDP identified two significant associations on chromosomes 4 and 10 with hepatic Malat1 ASO concentrations. Stabilin 2 (Stab2) and vesicle associated membrane protein 3 (Vamp3) were identified by cis-eQTL analysis. HMDP strains with lower Stab2 expression and Stab2 KO mice displayed significantly lower PK than strains with higher Stab2 expression and the wild type (WT) animals respectively, confirming the role of Stab2 in regulating hepatic Malat1 ASO uptake. GWA examining ASO efficacy uncovered three loci associated with Malat1 potency: Small Subunit Processome Component (Utp11l) on chromosome 4, Rho associated coiled-coil containing protein kinase 2 (Rock2) and Aci-reductone dioxygenase (Adi1) on chromosome 12. Our results demonstrate the utility of mouse GWAS using the HMDP in detecting genes capable of impacting the uptake of ASOs, and identifies genes critical for the activity of ASOs in vivo.

Asthma is a chronic inflammatory disease of the airways with contributions from genes, environmental exposures, and their interactions. While genome-wide association studies (GWAS) in humans have identified ~200 susceptibility loci, the genetic factors that modulate risk of asthma through gene-environment (GxE) interactions remain poorly understood. Using the Hybrid Mouse Diversity Panel (HMDP), we sought to identify the genetic determinants of airway hyperreactivity (AHR) in response to diesel exhaust particles (DEP), a model traffic-related air pollutant. As measured by invasive plethysmography, AHR under control and DEP-exposed conditions varied 3-4-fold in over 100 inbred strains from the HMDP. A GWAS with linear mixed models mapped two loci significantly associated with lung resistance under control exposure to chromosomes 2 (p = 3.0x10-6) and 19 (p = 5.6x10-7). The chromosome 19 locus harbors Il33 and is syntenic to asthma association signals observed at the IL33 locus in humans. A GxE GWAS for post-DEP exposure lung resistance identified a significantly associated locus on chromosome 3 (p = 2.5x10-6). Among the genes at this locus is Dapp1, an adaptor molecule expressed in immune-related and mucosal tissues, including the lung. Dapp1-deficient mice exhibited significantly lower AHR than control mice but only after DEP exposure, thus functionally validating Dapp1 as one of the genes underlying the GxE association at this locus. In summary, our results indicate that some of the genetic determinants for asthma-related phenotypes may be shared between mice and humans, as well as the existence of GxE interactions in mice that modulate lung function in response to air pollution exposures relevant to humans.

The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions.

Osteoporosis is a complex disorder and commonly leads to fractures in elderly persons. Genome-wide association studies (GWAS) have become an unbiased approach to identify variations in the genome that potentially affect health. However, the genetic variants identified so far only explain a small proportion of the heritability for complex traits. Due to the modest genetic effect size and inadequate power, true association signals may not be revealed based on a stringent genome-wide significance threshold. Here, we take advantage of SNP and transcript arrays and integrate GWAS and expression signature profiling relevant to the skeletal system in cellular and animal models to prioritize the discovery of novel candidate genes for osteoporosis-related traits, including bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), as well as geometric indices of the hip (femoral neck-shaft angle, NSA; femoral neck length, NL; and narrow-neck width, NW). A two-stage meta-analysis of GWAS from 7,633 Caucasian women and 3,657 men, revealed three novel loci associated with osteoporosis-related traits, including chromosome 1p13.2 (RAP1A, p = 3.6x10(-8)), 2q11.2 (TBC1D8), and 18q11.2 (OSBPL1A), and confirmed a previously reported region near TNFRSF11B/OPG gene. We also prioritized 16 suggestive genome-wide significant candidate genes based on their potential involvement in skeletal metabolism. Among them, 3 candidate genes were associated with BMD in women. Notably, 2 out of these 3 genes (GPR177, p = 2.6x10(-13); SOX6, p = 6.4x10(-10)) associated with BMD in women have been successfully replicated in a large-scale meta-analysis of BMD, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of our prioritization strategy. In the absence of direct biological support for identified genes, we highlighted the efficiency of subsequent functional characterization using publicly available expression profiling relevant to the skeletal system in cellular or whole animal models to prioritize candidate genes for further functional validation.

Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis were used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal, and femoral BMD revealed four significant associations (-log10P>5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12, and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism through which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cells of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.

Quantitative trait locus (QTL) analysis is a powerful tool for mapping genes for complex traits in mice, but its utility is limited by poor resolution. A promising mapping approach is association analysis in outbred stocks or different inbred strains. As a proof of concept for the association approach, we applied whole-genome association analysis to hepatic gene expression traits in an outbred mouse population, the MF1 stock, and replicated expression QTL (eQTL) identified in previous studies of F2 intercross mice. We found that the mapping resolution of these eQTL was significantly greater in the outbred population. Through an example, we also showed how this precise mapping can be used to resolve previously identified loci (in intercross studies), which affect many different transcript levels (known as eQTL "hotspots"), into distinct regions. Our results also highlight the importance of correcting for population structure in whole-genome association studies in the outbred stock.